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  • 1
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    Computational & mathematical organization theory 6 (2000), S. 395-410 
    ISSN: 1572-9346
    Keywords: organizational learning ; organizational structure ; organizational performance ; organizational models ; reengineering ; information overload ; simulation ; decision tasks
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The performance of various organizational structures is an essential parameter in the reengineering of organizations, particularly in the current rapidly changing, competitive and information technology-dependent environment. This situation has generally resulted in a smaller workforce confronted with voluminous information-processing requirements. Naturally, the focus has been on the design of organzations that will support effective and efficient learning processes. This specific study is on the contingency modely by Ouksel et al. (1997) on the impact of organizational structure on organizational learning and performance. It expands the empirical evaluation of the model to test its robustness. This is done by conducting extensive simulations with (a) a larger number of variables in the decision tasks, and (b) a larger set of numbers for each of the numeric variables, than has been used in the past. Overall, the validity of previous results achieved has been confirmed, but the selection of the most appropriate design, that which will indeed improve learning, is even more nuanced than past studies have concluded.
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  • 2
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    Computational & mathematical organization theory 6 (2000), S. 227-247 
    ISSN: 1572-9346
    Keywords: agent-based model ; technical change ; endogenous growth ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The factors which speed and slow technological innovation have been of interest to policy makers since at least the mid 1960's. Since that time, many theoretical models of innovation at the firm level and at the industry level have been proposed. Due to limitations in computational complexity, nearly all of these models have assumed a single, representative firm type. Very few have systematically investigated the implications of markets with a variety of firm types. With increases in computing power and the advent of agent-based modeling, interactions between agent types can now be explored. In this paper, a computational model of innovative firms in competitive markets is presented. Firms devote resources to R&D which can lead to new, improved products allowing firms to steal market share from their competitors. Two types of firms, differentiated by the strategies they use in pursuing new innovations, are allowed to coexist. One type pursues exclusively radical innovations, while the other pursues exclusively incremental innovations. It will be demonstrated that under certain conditions, a synergy exists between firms of different types which allows heterogeneous populations of firms to earn more than homogeneous ones.
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  • 3
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    Annals of operations research 94 (2000), S. 139-162 
    ISSN: 1572-9338
    Keywords: irrigated system ; modeling ; multi‐agent system ; simulation ; social networks ; coordination
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract The viability of irrigated systems in the Senegal River Valley is being brought into question today due to their under‐utilization. We assume that their viability depends largely on the way their different components behave and interact. We therefore sought to examine in greater depth today's knowledge of the structure of these systems and activities performed within them. This led to the development of a multi‐agent system model, a kind of virtual irrigated system, with a special focus on rules in use for access to credit, water allocation and cropping season assessment as well as organization and coordination of farmers. The purpose of this paper is to show how this kind of tool is relevant to the study of irrigated systems' viability. As an example it is used to examine the influence of existing social networks on the viability of irrigated systems.
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  • 4
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    Computational & mathematical organization theory 6 (2000), S. 339-360 
    ISSN: 1572-9346
    Keywords: virtual team ; virtual organization ; simulation ; coordination ; rework ; project duration ; team performance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract To date, efforts to understand virtual teaming have been largely anecdotal and atheoretical. Therefore, drawing from the extant research in the groups domain, we attempt to ground the definition of a virtual team in well-established group-level constructs, and design a simulation study to investigate the impact of different virtual team characteristics on team performance. Essentially, we argue that the virtual team is defined by three key characteristics—the virtual team context, the virtual team composition, and the virtual team structure. Using the VDT computational discrete event simulation model as our experimental platform, we simulated different virtual team models, and examined their impact on various team performance dimensions. We found that virtual team characteristics have different effects on different aspects of team performance. The virtual context team had a lower rework volume but higher coordination volume and longer project duration than the virtual composition team. Interestingly, we also found that the virtual structure team performed better than the software development team baseline model in all aspects of team performance. Based on these results, we proposed strategies to improve performance in different types of virtual team. Specifically, we propose (1) increasing the ease of communication and availability of routines in the virtual context team; (2) clarifying role expectations and fostering a team culture in the virtual composition team; and (3) implementing a lateral structure in the virtual team. Our results also suggest that firms should consider situational demands, specifically tolerance for errors and coordination volume, when considering the design of virtual teams.
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  • 5
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    Annals of the Institute of Statistical Mathematics 52 (2000), S. 438-447 
    ISSN: 1572-9052
    Keywords: Bessel distribution ; randomized gamma distribution ; von Mises-Fisher distribution ; Bessel quotient ; simulation ; path integral
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This article investigates basic properties of the Bessel distribution, a power series distribution which has not been fully explored before. Links with some well-known distributions such as the von Mises-Fisher distribution are described. A simulation scheme is also proposed to generate random samples from the Bessel distribution. This scheme is useful in Bayesian inferences and Monte Carlo computation.
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    Methodology and computing in applied probability 2 (2000), S. 5-21 
    ISSN: 1387-5841
    Keywords: directed pairwise-interaction point process ; directed Strauss process ; Markov random field ; simulation ; spatial point process
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper, we consider spatial point processes and investigate members of a subclass of the Markov point processes, termed the directed Markov point processes (DMPPs), whose joint distribution can be written in closed form and, as a consequence, its parameters can be estimated directly. Furthermore, we show how the DMPPs can be simulated rapidly using a one-pass algorithm. A subclass of Markov random fields on a finite lattice, called partially ordered Markov models (POMMs), has analogous structure to that of DMPPs. In this paper, we show that DMPPs are the limits of auto-Poisson and auto-logistic POMMs. These and other results reveal a close link between inference and simulation for DMPPs and POMMs.
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    Methodology and computing in applied probability 2 (2000), S. 37-58 
    ISSN: 1387-5841
    Keywords: optimization ; simulation ; Markov chain ; Monte Carlo
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We have recently developed a global optimization methodology for solving combinatorial problems with either deterministic or stochastic performance functions. This method, the Nested Partitions (NP) method has been shown to generate a Markov chain and with probability one to converge to a global optimum. In this paper, we study the rate of convergence of the method through the use of Markov Chain Monte Carlo (MCMC) methods, and use this to derive stopping rules that can be applied during simulation-based optimization. A numerical example serves to illustrate the feasibility of our approach.
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  • 8
    ISSN: 1573-8868
    Keywords: simulation ; nonlinear conditioning ; optimization ; FFT ; local perturbation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract A fast Fourier transform (FFT) moving average (FFT-MA) method for generating Gaussian stochastic processes is derived. Using discrete Fourier transforms makes the calculations easy and fast so that large random fields can be produced. On the other hand, the basic moving average frame allows us to uncouple the random numbers from the structural parameters (mean, variance, correlation length, ... ), but also to draw the randomness components in spatial domain. Such features impart great flexibility to the FFT-MA generator. For instance, changing only the random numbers gives distinct realizations all having the same covariance function. Similarly, several realizations can be built from the same random number set, but from different structural parameters. Integrating the FFT-MA generator into an optimization procedure provides a tool theoretically capable to determine the random numbers identifying the Gaussian field as well as the structural parameters from dynamic data. Moreover, all or only some of the random numbers can be perturbed so that realizations produced using the FFT-MA generator can be locally updated through an optimization process.
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  • 9
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    Discrete event dynamic systems 10 (2000), S. 271-294 
    ISSN: 1573-7594
    Keywords: resource allocation ; simulation ; optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Stochastic discrete resource allocation problems are difficult to solve. In this paper, we propose a new algorithm designed specifically to tackle them. The algorithm combines with the Nested Partitions method, the Ordinal Optimization techniques, and an efficient simulation control technique. The resulting hybrid algorithm retains the global perspective of the Nested Partitions method and the fast convergence properties of the Ordinal Optimization. Numerical results demonstrate that the hybrid algorithm can be effectively used for many large-scale stochastic discrete optimization problems.
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  • 10
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    Mathematical geology 32 (2000), S. 985-999 
    ISSN: 1573-8868
    Keywords: autorun ; fracture ; intact length ; quality ; rock ; simulation ; spacing
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract An important factor in the rock quality assessment analysis from discontinuity measurements along a scanline is the correlation of intact lengths. The autorun model and first order autorun coefficient are proposed as a method for objectively quantifying intact length correlation structure and discontinuity occurrences along any scanline. Necessary definitions for the methodology are presented on a quantitative basis such as the alternative intact length percentages and experimental autorun coefficient. An expression is proposed for the number of discontinuity occurrences along a scanline depending on the scanline length, alternate intact length percentages, and the autorun coefficient. Monte Carlo simulation technique is used with a suitable autorun model to verify this expression. A mathematical expression is derived for the expected Rock Quality Designation (RQD) value by taking into account the correlation of the intact lengths. Additional simulations show the validity of the new RQD expression. With the methodology proposed much less engineering experience and judgment are required in estimating the RQD value from scanline measurements. The application of the methodology has been presented for some field data.
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  • 11
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    Mathematical geology 32 (2000), S. 367-379 
    ISSN: 1573-8868
    Keywords: random functions ; simulation ; geostatistics
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract This paper presents a new method of constructing random functions whose realizations can be evaluated efficiently. The basic idea is to “blend,” both stochastically and linearly, a limited set of independent initial realizations previously generated by any chosen simulation method. The blending stochastic coefficients are determined in such a way that the new random function so generated has the same mean and covariance functions as the random function used for generating the initial realizations.
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    Applied mathematics and mechanics 21 (2000), S. 425-432 
    ISSN: 1573-2754
    Keywords: general failure probability ; simulation ; failure mode ; V215.7 ; V214.4
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics , Mathematics , Physics
    Notes: Abstract A general failure probability simulation and deviation evaluation methods were presented for fuzzy safety state and fuzzy failure state. And the corresponding number integral method was simultaneously established. As the distribution of state variable and the membership of the state variable to the fuzzy safety set were normal, the general failure probability of the single failure mode had precise analytic solution, which was used to verify the precision of the presented methods. The results show that the evaluation of the simulation method convergences to the analytic solution with the number increase of the sampling. The above methods for the single failure mode was extended to the multi-mode by the expansion and probability principles. The presented methods were applied to the engineering problem. For the number of significant mode is not too many, the high precision solution can be given by the presented number simulation and number integral methods, which is illustrated by the engineering examples. In addition, the application scope of the methods was discussed.
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    Statistics and computing 10 (2000), S. 121-132 
    ISSN: 1573-1375
    Keywords: random sets ; random structures ; Boolean model ; Boolean random functions ; dead leaves model ; simulation ; image analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract We consider the construction and properties of some basic random structure models (point processes, random sets and random function models) for the description and for the simulation of heterogeneous materials. They can be specialized to three dimensional Euclidean space. Their implementation requires the use of image analysis tools.
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    Statistics and computing 10 (2000), S. 245-252 
    ISSN: 1573-1375
    Keywords: estimation of means ; sample mean ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Consider the random sampling of a discrete population. The observations, as they are collected one by one, are enhanced in that the probability mass associated with each observation is also observed. The goal is to estimate the population mean. Without this extra information about probability mass, the best general purpose estimator is the arithmetic average of the observations, XBAR. The issue is whether or not the extra information can be used to improve on XBAR. This paper examines the issues and offers four new estimators, each with its own strengths and liabilities. Some comparative performances of the four with XBAR are made. The motivating application is a Monte Carlo simulation that proceeds in two stages. The first stage independently samples n characteristics to obtain a “configuration” of some kind, together with a configuration probability p obtained, if desired, as a product of n individual probabilities. A relatively expensive calculation then determines an output X as a function of the configuration. A random sample of X could simply be averaged to estimate the mean output, but there are possibly more efficient estimators on account of the known configuration probabilities.
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    Computational & mathematical organization theory 5 (1999), S. 167-192 
    ISSN: 1572-9346
    Keywords: rational choice ; friendship ; Markov processes ; random utility models ; simulation ; empirical test
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We propose a class of actor-oriented statistical models for closed social networks in general, and friendship networks in particular. The models are random utility models developed within a rational choice framework. Based on social psychological and sociological theories about friendship, mathematical functions capturing expected utility of individual actors with respect to friendship are constructed. Expected utility also contains a random (unexplained) component. We assume that, given their restrictions and contact opportunities, individuals evaluate their utility functions and behave such that they maximize the expected amount of utility. The behavior under consideration is the expression of like and dislike (choice of friends). Theoretical mechanisms that are modelled are, e.g., the principle of diminishing returns, the tendency towards reciprocated choices, and the preference for friendship relations with similar others. Constraints imposed on individuals are, e.g., the structure of the existing network, and the distribution of personal characteristics over the respondents. The models are illustrated by means of a data-set collected among university freshmen at 7 points in time during 1994 and 1995.
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    Journal of computational analysis and applications 1 (1999), S. 349-385 
    ISSN: 1572-9206
    Keywords: Estimation ; geometric compound ; heavy-tail modeling ; Linnik distribution ; Mittag–Leffler law ; mixture ; multivariate Laplace distribution ; random summation ; simulation ; subordination
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The paper discusses recent advances in the theory of multivariate geometric stable (GS) distributions. The results presented include characterizations, mixture representations, properties, simulation, and estimation.
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    Methodology and computing in applied probability 1 (1999), S. 127-190 
    ISSN: 1387-5841
    Keywords: combinatorial optimization ; global optimization ; importance sampling ; markov chain monte carlo ; simulated annealing ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We present a new and fast method, called the cross-entropy method, for finding the optimal solution of combinatorial and continuous nonconvex optimization problems with convex bounded domains. To find the optimal solution we solve a sequence of simple auxiliary smooth optimization problems based on Kullback-Leibler cross-entropy, importance sampling, Markov chain and Boltzmann distribution. We use importance sampling as an important ingredient for adaptive adjustment of the temperature in the Boltzmann distribution and use Kullback-Leibler cross-entropy to find the optimal solution. In fact, we use the mode of a unimodal importance sampling distribution, like the mode of beta distribution, as an estimate of the optimal solution for continuous optimization and Markov chains approach for combinatorial optimization. In the later case we show almost surely convergence of our algorithm to the optimal solution. Supporting numerical results for both continuous and combinatorial optimization problems are given as well. Our empirical studies suggest that the cross-entropy method has polynomial in the size of the problem running time complexity.
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    Journal of nondestructive evaluation 18 (1999), S. 117-126 
    ISSN: 1573-4862
    Keywords: Nondestructive evaluation ; layered cylindrical structures ; cylindrical waves ; simulation ; inverse problem
    Source: Springer Online Journal Archives 1860-2000
    Topics: Electrical Engineering, Measurement and Control Technology , Mathematics
    Notes: Abstract For the characterization of the unknown material properties of a layered cylindrical structure, axially symmetric wave signals transmitted and reflected by the structure have been used. Since only a single wave mode propagates in the structure, the measurement and analysis of the transmitted and reflected signals can be simplified significantly. The evaluation of the material properties of the layers can be achieved with great accuracy. In this paper, we first derive the transmission and reflection coefficients for the layered cylindrical structure sonified axisymmetrically by an incident cylindrical wave. We then relate the spectra of the transmitted and reflected wave signals to the transmission and reflection coefficients as ratio functions. The time-domain signals transmitted and reflected by the structure can then be reconstructed from a routine application of the Fourier integrals. A three-layered aluminum/epoxy/aluminum tube is used to illustrate the application of the expressions for both the forward and inverse problems. The results show that the technique developed in this study can be used very effectively for the characterization of layered cylindrical structures.
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    Discrete event dynamic systems 9 (1999), S. 261-284 
    ISSN: 1573-7594
    Keywords: discrete event dynamic systems ; simulation ; communications ; performance analysis ; alignment
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In the design and optimization of discrete event dynamic systems, it is often necessary to order alternative designs based on their relative performance, i.e., to rank them from best to worst. In this paper, alignment of observed performance orders with true orders is considered and properties of the alignment are investigated. Spearman's rank correlation coefficient is a measure of agreement between the observed performance orders and the true ones. It is shown that Spearman's coefficient converges exponentially in the simulation time or observation time, which gives a strong evidence of the efficiency of order comparison for discrete event dynamic systems. In the context of simulation, the effect of simulation dependence on the alignment is also discussed. It is found that neither independent simulation nor the scheme of common random numbers (CRN), a popular scheme for variance reduction, can yield dominant performance. Finally, numerical examples based on a networking optimization problem are provided to illustrate the convergence of Spearman's coefficient. In these examples, the standard clock (SC) simulation technique provides much faster convergence than either independent simulations or CRN simulations. Both the SC and CRN methods use the same random number sequence to drive many events in parallel; however, under SC the events driving the parallel experiments are all identical, whereas under CRN they may be different.
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  • 20
    ISSN: 1573-8868
    Keywords: simulation ; conditional simulation ; fourier methods ; band-limited fractal ; variogram ; fast kriging
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract We evaluate the performance and statistical accuracy of the fast Fourier transform method for unconditional and conditional simulation. The method is applied under difficult but realistic circumstances of a large field (1001 by 1001 points) with abundant conditioning criteria and a band limited, anisotropic, fractal-based statistical characterization (the von Kármán model). The simple Fourier unconditional simulation is conducted by Fourier transform of the amplitude spectrum model, sampled on a discrete grid, multiplied by a random phase spectrum. Although computationally efficient, this method failed to adequately match the intended statistical model at small scales because of sinc-function convolution. Attempts to alleviate this problem through the “covariance” method (computing the amplitude spectrum by taking the square root of the discrete Fourier transform of the covariance function) created artifacts and spurious high wavenumber content. A modified Fourier method, consisting of pre-aliasing the wavenumber spectrum, satisfactorily remedies sinc smoothing. Conditional simulations using Fourier-based methods require several processing stages, including a smooth interpolation of the differential between conditioning data and an unconditional simulation. Although kriging is the ideal method for this step, it can take prohibitively long where the number of conditions is large. Here we develop a fast, approximate kriging methodology, consisting of coarse kriging followed by faster methods of interpolation. Though less accurate than full kriging, this fast kriging does not produce visually evident artifacts or adversely affect the a posteriori statistics of the Fourier conditional simulation.
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    Journal of optimization theory and applications 103 (1999), S. 137-159 
    ISSN: 1573-2878
    Keywords: Stochastic optimization ; simulation ; estimation ; time-varying objective functions ; discrete event dynamic systems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper, the optimization of time-varying objective functions, known only through estimates, is considered. Recent research defined algorithms for static optimization problems. Based on one of these algorithms, we derive an optimization scheme for the time-varying case. In stochastic optimization problems, convergence of an algorithm to the optimum prevents the algorithm from being efficiently adaptive to changes of the objective function if it is time-varying. So, convergence cannot be required in a time-varying scenario. Rather, we require convergence to the optimum with high probability together with a satisfactory dynamical behavior. Analytical and simulative results illustrate the performance of the proposed algorithm compared with other optimization techniques.
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    Computational & mathematical organization theory 3 (1998), S. 219-247 
    ISSN: 1572-9346
    Keywords: computational models of organizations ; organizational ecology ; cellular automata ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Research on the ecological dynamics oforganizational populations has demonstrated that competitiveconditions at the time of founding have enduring effects onorganizational survival. According to ecological theories,organizational life chances are systematically affected by density (the number of organizations in a population) at thetime of founding because the lower resource endowments thatcharacterize organizations appearing in periods of highpopulation density tend to become self-reinforcing, and—over time—amplify differences in mortality rates oforganizations founded under different conditions. However,credible arguments have been offered that could justify both positive and negative effects of the delayed effectsof population density on organizational mortality rates, andreceived empirical research in part reflects this ambiguity.To develop new insight into this issue and to explore theboundaries of received empirical results, in this study wepresent a computational model of organizational evolutionaccording to which the global dynamics of organizationalpopulations emerge from the iteration of simple rules oflocal interaction among individual organizations. We use the synthetic data produced by simulation to estimate eventhistory models of organizational mortality, and compare theparameter estimates with those reported in the most recentempirical studies of actual organizational populations. Theconclusions supported by the model qualify and extendreceived empirical results, and suggest that delayed effectsof density are highly sensitive the details of local structure of connections among members of organizationalpopulations.
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    Computational & mathematical organization theory 4 (1998), S. 43-69 
    ISSN: 1572-9346
    Keywords: simulation ; organization ; computational model ; formal logic ; cognition
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A programming language which is optimized for modelling multi-agent interaction within articulated social structures such as organizations is described with several examples of its functionality. The language is SDML, a strictly declarative modelling language which has object-oriented features and corresponds to a fragment of strongly grounded autoepistemic logic. The virtues of SDML include the ease of building complex models and the facility for representing agents flexibly as models of cognition as well as modularity and code reusability. Two representations of cognitive agents within organizational structures are reported and a Soar-to-SDML compiler is described. One of the agent representations is a declarative implementation of a Soar agent taken from the Radar-Soar model of Ye and Carley (1995). The Ye-Carley results are replicated but the declarative SDML implementation is shown to be much less computationally expensive than the more procedural Soar implementation. As a result, it appears that SDML supports more elaborate representations of agent cognition together with more detailed articulation of organizational structure than we have seen in computational organization theory. Moreover, by representing Soar-cognitive agents declaratively within SDML, that implementation of the Ye-Carley specification is necessarily consistent and sound with respect to the formal logic to which SDML corresponds.
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    Computational & mathematical organization theory 4 (1998), S. 71-95 
    ISSN: 1572-9346
    Keywords: organization modeling ; health care ; simulation ; medical protocols ; representation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Organizational simulations have been used in business, manufacturing, and engineering design tasks to gain insight into organizational process bottlenecks, and to improve the quality and efficiency of processes within these industries. As market pressures demand increased efficiencies within the health care industry, organizational simulation techniques could provide similar insight into the design of better medical care processes, or protocols, in medical organizations. To simulate the process of medical care within a specific organization however, requires models that can represent (1) unpredictable patient responses to care, (2) the flexibility needed to adapt to different patients, and (3) different preferences of health care professionals and the implicit preferences contained within the protocol. Using previous work on simulation in the Virtual Design Team (VDT), and an example protocol drawn from an existing protocol in bone marrow transplantation, we describe extensions to the VDT information-processing representation that will allow us to simulate the performance characteristics of a medical protocol used within a medical organization. Our representational extensions capture the uncertainty of medical care for patients, the activity flexibility within the organization, and the preferences of health care professionals that will make information-processing organizational simulations in the medical domain possible. We believe our representation will provide a robust simulation “tool box” that can be used to investigate the performance of specific medical protocols within different hospital settings, and explore organizational theory within the health care industry.
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    Extremes 1 (1998), S. 111-126 
    ISSN: 1572-915X
    Keywords: Poisson process ; scan statistic ; approximation ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Given a Poisson process in two or three dimensions, we are interested in the scan statistic, i.e. the largest number of points contained in a translate of a fixed scanning set restricted to lie inside a rectangular area. The distribution of the scan statistic is accurately approximated for rectangular scanning sets, using a technique that is also extended to higher dimensions. The accuracy of the approximation is checked through simulation.
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    Nonlinear dynamics 16 (1998), S. 349-368 
    ISSN: 1573-269X
    Keywords: Dynamic parameters ; multibody dynamics ; four-bar mechanism ; simulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Dynamic equations of motion require a large number of parameters for each element of the system. These can include for each part their mass, location of center of mass, moment of inertia, spring stiffnesses and damping coefficients. This paper presents a technique for estimating these parameters in spatial mechanisms using any joint type, based on measurements of displacements, velocities and accelerations and of external forces and torques, for the purpose of building accurate multibody models of mechanical systems. A form of the equations of spatial motion is derived, which is linear in the dynamic parameters and based on multibody simulation code methodologies. Singular value decomposition is used to find the ‘essential parameter set’, and ‘minimum parameter set’. It is shown that a simulation of a four-bar mechanism (with spherical, universal, and revolute joints) and based on the estimated parameters gives accurate response.
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    Nonlinear dynamics 17 (1998), S. 187-203 
    ISSN: 1573-269X
    Keywords: Gear ; stochastic vibration ; Markov process ; simulation
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    Topics: Mathematics
    Notes: Abstract A dynamic and stochastic simulation model is developed for analyzing the vibration of gear transmission systems with consideration of the influence of the time-variant stiffness, loads, and gear transmission errors. The gear transmission system is viewed as a non-linear, time-correlated and stationary stochastic system. The transmission errors of gears are decomposed into harmonic and random components based on the spectral analysis. To simulate the random component, a second order Markov process with time-variant parameters considering influence of rotational speed is proposed and the method to determine the model parameters based on the random error of measured gear transmission error is developed. A simulation system is developed. The input to the simulation system is a white Gaussian noise process and harmonic errors, and the output is the rotational vibration acceleration of gears. Experiments are carried out to verify the proposed model. The influences of the random error on vibration acceleration are examined using the developed simulation system.
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    OR spectrum 19 (1997), S. 23-29 
    ISSN: 1436-6304
    Keywords: Job shop scheduling ; dispatching rules ; coordination ; look ahead information ; simulation ; Werkstattsteuerung ; Steuerungsregeln ; Koordination ; Vorausschauende Informationen ; Simulation
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    Topics: Mathematics , Economics
    Description / Table of Contents: Zusammenfassung In diesem Beitrag wird ein neuartiger Ansatz zur Koordination dezentraler Werkstattsteuerungsregeln vorgestellt und mit Hilfe einer Simulationsstudie analysiert. Die Koordination basiert auf vorausschauenden Informationen und enthält einen Auftragsnachfrage-/-angebotsmechanismus. Die Simulations-experimente zeigen, daß durch den Einsatz des Koordinationsmechanismus die Leistung herkömmlicher Steuerungsregeln signifikant verbessert wird.
    Notes: Abstract In this paper a new coordination approach for decentralized job shop scheduling rules is presented and analyzed in a simulation study. The coordination is based on look ahead information and contains a mechanism for demanding and supplying jobs. The simulation experiments show that the performance of conventional scheduling rules is significantly improved using the coordination mechanism.
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    OR spectrum 19 (1997), S. 23-29 
    ISSN: 1436-6304
    Keywords: Key words: Job shop scheduling ; dispatching rules ; coordination ; look ahead information ; simulation ; Schlüsselwörter: Werkstattsteuerung ; Steuerungsregeln ; Koordination ; Vorausschauende Informationen ; Simulation
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    Topics: Mathematics , Economics
    Description / Table of Contents: Zusammenfassung. In diesem Beitrag wird ein neu-artiger Ansatz zur Koordination dezentraler Werkstattsteuerungsregeln vorgestellt und mit Hilfe einer Simulationsstudie analysiert. Die Koordination basiert auf vorausschauenden Informationen und enthält einen Auftragsnachfrage-/-angebotsmechanismus. Die Simulations- experimente zeigen, daß durch den Einsatz des Koordinationsmechanismus die Leistung herkömmlicher Steuerungsregeln signifikant verbessert wird.
    Notes: Abstract. In this paper a new coordination approach for decentralized job shop scheduling rules is presented and analyzed in a simulation study. The coordination is based on look ahead information and contains a mechanism for demanding and supplying jobs. The simulation experiments show that the performance of conventional scheduling rules is significantly improved using the coordination mechanism.
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    ISSN: 1572-9338
    Keywords: integer programming ; discriminant analysis ; simulation
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    Notes: Abstract Although there have been several journal articles on the classificatory performance of mathematical programming approaches to the two-group discriminant problem, there has been no simulation study on the classificatory performance of mathematical programming approaches to the multiple-group problem reported in the literature. This study reports the results of a simulation experiment on the classificatory performance of a single-function and a multiple-function mathematical programming model relative to that of the standard parametric procedures for the three-group problem with small training samples. The effect of second-order terms on the classificatory performance of the mathematical programming models for the three-group problem is also investigated. Furthermore, this study theoretically examines the range of parameter values of a multiple-function mathematical programming model for which its number of misclassifications in the training sample cannot exceed that of a single-function model.
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    Annals of operations research 74 (1997), S. 321-332 
    ISSN: 1572-9338
    Keywords: simulation ; modeling ; aerospace ; air route structure ; free flight ; clustering
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    Topics: Mathematics , Economics
    Notes: Abstract Recent work performed for the Federal Aviation Administration to support the development of future concepts of air traffic management has involved simulation modeling of patterns of airspace usage by commercial and business air traffic. The objective of these efforts has been to investigate the impacts of a pattern of airspace usage known as "free flight", whereby pilots and flight dispatchers have much more freedom to choose, say, direct or wind-optimal routing through airspace. One of the figures of merit investigated is a count of "convergence pairs" as a measure of the complexity of various traffic patterns. These are cases when aircraft in the simulation model fly close to each other. Interestingly, geographic plots of convergence pairs accumulated over time bring out certain features or patterns of congested air traffic flows or flight alignments. However, these plots are also thick with "noise" or extraneous convergence pairs, whose presence detracts from the ability to perceive congested air traffic flows. Cluster analysis has been found to be an effective method of filtering these displays so that the congested flow features are discernible. The process developed for this purpose is based on a two-pass clustering approach. The process has worked well for the simulation modeling performed to date. Classification of the locations of convergence pairs into congested flow corridors is visually appealing, and has helped distinguish differences in contrasting scenarios of airspace usage. The paper presents graphical results and describes the clustering algorithms employed.
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    Computational & mathematical organization theory 3 (1997), S. 151-171 
    ISSN: 1572-9346
    Keywords: organizational performance ; planned organizational change ; resistance to change ; system dynamics ; simulation
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    Topics: Mathematics
    Notes: Abstract This paper suggests that an induction of change program leads to atemporary impairment of organizational performance. A System Dynamics Modelportrays the process of planned organizational change. A set of keyvariables that facilitate or impede change is identified, quantified, andintegrated into the model. Three data sets, reproduced by simulation,demonstrate that the model is internally consistent and empiricallyadequate. The paper discusses theoretical and practical implications of the‘initial dip’ phenomenon in processes of planned change.
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    Annals of operations research 74 (1997), S. 239-257 
    ISSN: 1572-9338
    Keywords: autocorrelation ; L 1 regression ; least absolute deviations ; robust regression ; simulation
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    Topics: Mathematics , Economics
    Notes: Abstract Least absolute value (LAV) regression provides a robust alternative to least squares, particularly when the disturbances follow distributions that are nonnormal and subject to outliers. While inference in least squares estimation is well-understood, inferential procedures in the context of LAV estimation have not been studied as extensively, particularly in the presence of non-independent disturbances. In this work, we study three alternative significance test procedures in LAV regression, along with two approaches used to correct for serial correlation. The study is based on large-scale Monte Carlo simulations, and comparisons are made based on both observed significance levels and power.
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    Annals of operations research 73 (1997), S. 233-252 
    ISSN: 1572-9338
    Keywords: Data Envelopment Analysis ; model specification ; simulation
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    Notes: Abstract The use of Data Envelopment Analysis for estimating comparative efficiency has become widespread, and there has been considerable academic attention paid to the development of variants of the basic DEA model. However, one of the principal weaknesses of DEA is that - unlike statistically based methods - it yields no diagnostics to help the user determine whether or not the chosen model is appropriate. In particular, the choice of inputs and out-puts depends solely on the judgement of the user. The purpose of this paper is to examine the implications for efficiency scores of using a misspecified model. A simple production process is set up. Simulation models are then used to explore the effects of applying misspecified DEA models to this process. The phenomena investigated are: the omission of significant variables; the inclusion of irrelevant variables; and the adoption of an inappropriate variable returns to scale assumption. The robustness of the results is investigated in relation to sample size; variations in the number of inputs; correlation between inputs; and variations in the importance of inputs. The paper concludes that the dangers of misspecification are most serious when simple models are used and sample sizes are small. In such circumstances, it is concluded that it will usually be to the modeller's advantage to err on the side of including possibly irrelevant variables rather than run the risk of excluding a potentially important variable from the model.
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    Mathematical geology 29 (1997), S. 993-1008 
    ISSN: 1573-8868
    Keywords: lognormal estimator ; lognormal kriging ; simulation ; conditional unbiasedness ; robustness
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    Topics: Geosciences , Mathematics
    Notes: Abstract In an open pit mine, the selection of blocks for mill feed necessitates the use of a conditionally unbiased estimator not only to maximize profits, but also to predict precisely the grades at the mill. Estimation of blocks usually is done using a series of blasthole assays on a regular grid. In many instances, the blasthole grades show a lognormal-like distribution. This study examines an estimator based on the hypothesis of bilognormality between the true block grade and the estimate obtained using the blastholes. The properties of the estimator are established and the estimator is proven to be conditionally unbiased. It is almost as precise as the lognormal kriging estimator when the points are multilognormal. However, it is more precise than lognormal krigings when only univariate lognormality is present or when the distribution is not exactly lognormal. The estimator also is shown to be robust to errors in the specifications of the variogram model or of the expectation of Z. Contrary to lognormal krigings, the estimator does only a slight correction to the original estimate obtained using the blastholes assays.
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    Journal of optimization theory and applications 93 (1997), S. 455-489 
    ISSN: 1573-2878
    Keywords: Subset selection ; stochastic optimization ; alignment probability ; ordered performance curve ; simulation ; modeling
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    Notes: Abstract We examine in this paper the subset selection procedure in the context of ordinal optimization introduced in Ref. 1. Major concepts including goal softening, selection subset, alignment probability, and ordered performance curve are formally introduced. A two-parameter model is devised to calculate alignment probabilities for a wide range of cases using two different selection rules: blind pick and horse race. Our major result includes the suggestion of quantifiable subset selection sizes which are universally applicable to many simulation and modeling problems, as demonstrated by the examples in this paper.
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    Nonlinear dynamics 12 (1997), S. 367-397 
    ISSN: 1573-269X
    Keywords: Flexible ; simulation ; multibody ; dynamics
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    Notes: Abstract The modelling of flexible elements in mechanical systems has been widely investigated through several methods issuing from both the area of structural mechanics and the field of multibody dynamics. As regards the latter discipline, beside the problem of the generation of the multibody equations of motion, the choice of a spatial discretization method for modelling flexible elements has always been considered as a critical phase of the modelling. Although this subject is abundantly tackled in the open-literature, the latter probably lacks an objective comparison between the most commonly used approaches. This contribution presents an extensive investigation of several discretization techniques of flexible beams, in a pure multibody context. In particular, it is shown that shape functions based on power series monomials are very suitable and versatile to model beams being part of a multibody system and thus constitutes an interesting alternative to finite element analysis. For this purpose, a symbolic multibody program, in which various discretization techniques were implemented, was generalized to compute the equations of motion of a general multibody system containing flexible beams.
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    Annals of operations research 67 (1996), S. 183-210 
    ISSN: 1572-9338
    Keywords: Capacity planning ; emergency services ; health care ; simulation
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    Topics: Mathematics , Economics
    Notes: Abstract Due to its highly stochastic nature and complex interaction between services involved, health care has been a demanding area of application for computer simulation. This paper includes details and results of a simulation study realized in the Surgical Emergency Department at Istanbul University School of Medicine. The purpose is to suggest new bed capacities to improve the current system, and also to provide the management with guidelines for their expansion plans. For this aim, arrival rates, treatment procedures, inpatient admittance, and service durations have been carefully analyzed and modeled. The model, coded in SLAM-II simulation language, has been run under several bed capacity scenarios, and resulting queueing and waiting patterns have been discussed in detail.
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    Computational & mathematical organization theory 2 (1996), S. 171-195 
    ISSN: 1572-9346
    Keywords: organization design ; simulation ; organization modeling ; organizational analysis tools
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    Notes: Abstract Large scale and multidisciplinary engineering projects (e.g., design of a hospital building) are often complex. They usually involve many interdependent activities and require intensive coordination among actors (i.e., designers) to deal with activity interdependencies. To make such projects more effective and efficient, one needs to understand how coordination requirements are generated and what coordination mechanisms should be applied for given project situations. Our research on the Virtual Design Team (VDT) attempts to develop a computational model of project organizations to analyze how activity interdependencies raise coordination needs and how organization design and communication tools change team coordination capacity and project performance. The VDT model is built based on contingency theory (Galbraith, 1977) and our observations about collaborative and multidisciplinary work in large, complex projects. VDT explicitly models actors, activities, communication tools and organizations. Based on our extended information-processing view of organizations, VDT simulates the actions of, and interactions among actors as processes of attention allocation, capacity allocation, and communication. VDT evaluates organization performance by measuring emergent project duration, direct cost, and coordination quality. The VDT model has been tested internally, and evaluated externally through case-studies. We found three way qualitative consistency among predictions of the simulation model, of organization theory, and of experienced project managers. In this paper, we present the VDT model in detail and discuss some general issues involved in computational organization modeling, including level of abstraction of tasks and actors' reasoning, and model validation.
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    Finance and stochastics 1 (1996), S. 25-41 
    ISSN: 1432-1122
    Keywords: Key words: Martingale estimating function ; option pricing ; quasi-likelihood ; simulation ; stochastic differential equation ; volatility. ; JEL classification: G12 ; Mathematics Subject Classification (1991): 62M05
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    Topics: Mathematics , Economics
    Notes: Abstract. In the present paper we consider a model for stock prices which is a generalization of the model behind the Black–Scholes formula for pricing European call options. We model the log-price as a deterministic linear trend plus a diffusion process with drift zero and with a diffusion coefficient (volatility) which depends in a particular way on the instantaneous stock price. It is shown that the model possesses a number of properties encountered in empirical studies of stock prices. In particular the distribution of the adjusted log-price is hyperbolic rather than normal. The model is rather successfully fitted to two different stock price data sets. Finally, the question of option pricing based on our model is discussed and comparison to the Black–Scholes formula is made. The paper also introduces a simple general way of constructing a zero-drift diffusion with a given marginal distribution, by which other models that are potentially useful in mathematical finance can be developed.
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    Mathematical geology 28 (1996), S. 723-734 
    ISSN: 1573-8868
    Keywords: simulation ; probability field ; uniform transform ; filtering ; histogram reproduction
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    Topics: Geosciences , Mathematics
    Notes: Abstract A combination of factorial kriging and probability field simulation is proposed to correct realizations resulting from any simulation algorithm for either too high nugget effect (noise) or poor histogram reproduction. First, a factorial kriging is done to filter out the noise from the noisy realization. Second, the uniform scores of the filtered realization are used as probability field to sample the local probability distributions conditional to the same dataset used to generate the original realization. This second step allows to restore the data variance. The result is a corrected realization which reproduces better target variogram and histogram models, yet honoring the conditioning data.
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    Statistics and computing 6 (1996), S. 277-287 
    ISSN: 1573-1375
    Keywords: Bayesian inference ; contingency tables ; Gibbs sampling ; graphical methods ; hypothesis testing ; independence ; intraclass tables ; model comparison ; predictive densities ; quasisymmetry ; simulation
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    Topics: Computer Science , Mathematics
    Notes: Abstract In this paper we present a simulation and graphics-based model checking and model comparison methodology for the Bayesian analysis of contingency tables. We illustrate the approach by testing the hypotheses of independence and symmetry on complete and incomplete simulated tables.
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    Journal of optimization theory and applications 91 (1996), S. 363-388 
    ISSN: 1573-2878
    Keywords: Stochastic optimization ; simulation ; discrete event dynamic systems
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    Topics: Mathematics
    Notes: Abstract Recent research has demonstrated that ordinal comparison has fast convergence despite the possible presence of large estimation noise in the design of discrete event dynamic systems. In this paper, we address the fundamental problem of characterizing the convergence of ordinal comparison. To achieve this goal, an indicator process is formulated and its properties are examined. For several performance measures frequently used in simulation, the rate of convergence for the indicator process is proven to be exponential for regenerative simulations. Therefore, the fast convergence of ordinal comparison is supported and explained in a rigorous framework. Many performance measures of averaging type have asymptotic normal distributions. The results of this paper show that ordinal comparison converges monotonically in the case of averaging normal random variables. Such monotonicity is useful in simulation planning.
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    Journal of optimization theory and applications 91 (1996), S. 585-615 
    ISSN: 1573-2878
    Keywords: Stochastic optimization ; simulation ; estimation ; stochastic comparison ; simulated annealing
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    Topics: Mathematics
    Notes: Abstract The problem of stochastic optimization for arbitrary objective functions presents a dual challenge. First, one needs to repeatedly estimate the objective function; when no closed-form expression is available, this is only possible through simulation. Second, one has to face the possibility of determining local, rather than global, optima. In this paper, we show how the stochastic comparison approach recently proposed in Ref. 1 for discrete optimization can be used in continuous optimization. We prove that the continuous stochastic comparison algorithm converges to an ∈-neighborhood of the global optimum for any ∈〉0. Several applications of this approach to problems with different features are provided and compared to simulated annealing and gradient descent algorithms.
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    Statistics and computing 6 (1996), S. 85-92 
    ISSN: 1573-1375
    Keywords: Cluster analysis ; Conditional Gaussian distribution ; EM algorithm ; graphical modelling ; location model ; mixture maximum likelihood ; simulation
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    Topics: Computer Science , Mathematics
    Notes: Abstract One possible approach to cluster analysis is the mixture maximum likelihood method, in which the data to be clustered are assumed to come from a finite mixture of populations. The method has been well developed, and much used, for the case of multivariate normal populations. Practical applications, however, often involve mixtures of categorical and continuous variables. Everitt (1988) and Everitt and Merette (1990) recently extended the normal model to deal with such data by incorporating the use of thresholds for the categorical variables. The computations involved in this model are so extensive, however, that it is only feasible for data containing very few categorical variables. In the present paper we consider an alternative model, known as the homogeneous Conditional Gaussian model in graphical modelling and as the location model in discriminant analysis. We extend this model to the finite mixture situation, obtain maximum likelihood estimates for the population parameters, and show that computation is feasible for an arbitrary number of variables. Some data sets are clustered by this method, and a small simulation study demonstrates characteristics of its performance.
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    ISSN: 1573-7594
    Keywords: optimization ; standard clock ; ordinal optimization ; communication network ; voice/data integration ; simulation
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    Topics: Mathematics
    Notes: Abstract In this paper we apply the ideas of ordinal optimization and the technique of Standard Clock (SC) simulation to the voice-call admission-control problem in integrated voice/data multihop radio networks. This is an important problem in networking that is not amenable to exact analysis by means of the usual network modeling techniques. We first describe the use of the SC approach on sequential machines, and quantify the speedup in simulation time that is achieved by its use in a number of queueing examples. We then develop an efficient simulation model for wireless integrated networks based on the use of the SC approach, which permits the parallel simulation of a large number of admission-control policies, thereby reducing computation time significantly. This model is an extension of the basic SC approach in that it incorporates fixed-length data packets, whereas SC simulation is normally limited to systems with exponentially distributed interevent times. Using this model, we demonstrate the effectiveness of ordinal-optimization techniques, which provide a remarkably good ranking of admission-control policies after relatively short simulation runs, thereby facilitating the rapid determination of good policies. Moreover, we demonstrate that the use of crude, inaccurate analytical and simulation models can provide highly accurate policy rankings that can be used in conjunction with ordinal-optimization methods, provided that they incorporate the key aspects of system operation.
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    Mathematical geology 27 (1995), S. 149-172 
    ISSN: 1573-8868
    Keywords: uncertainty models ; conditional distributions ; simulation ; variogram ; kriging
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    Topics: Geosciences , Mathematics
    Notes: Abstract Approximate local confidence intervals are constructed from uncertainty models in the form of the conditional distribution of the random variable Z given values of variables [Zi, i=1,...,n]. When the support of the variable Z is any support other than that of the data, the conditional distributions require a change of support correction. This paper investigates the effect of change of support on the approximate local confidence intervals constructed by cumulative indicator kriging, class indicator kriging, and probability kriging under a variety of conditions. The conditions are generated by three simulated deposits with grade distributions of successively higher degree of skewness; a point support and two different block supports are considered. The paper also compares the confidence intervals obtained from these methods using the most used measures of confidence interval effectiveness.
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    Annals of operations research 53 (1994), S. 175-197 
    ISSN: 1572-9338
    Keywords: Variance reduction ; simulation ; control variates ; importance sampling ; common random numbers ; stratification ; conditioning ; efficiency
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    Topics: Mathematics , Economics
    Notes: Abstract This paper provides an overview of the five most commonly used statistical techniques for improving the efficiency of stochastic simulations: control variates, common random numbers, importance sampling, conditional Monte Carlo, and stratification. The paper also describes a mathematical framework for discussion of efficiency issues that quantifies the trade-off between lower variance and higher computational time per observation.
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    Annals of operations research 53 (1994), S. 391-418 
    ISSN: 1572-9338
    Keywords: Autoregressive process ; confidence interval ; output analysis ; simulation ; statistics ; time series
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    Topics: Mathematics , Economics
    Notes: Abstract We revisit and update the autoregressive-output-analysis method for constructing a confidence interval for the steady-state mean of a simulated process by using Rissanen's predictive least-squares criterion to estimate the autoregressive order of the process. This order estimator is strongly consistent when the output is autoregressive. The order estimator is combined with the standard autoregressive-output-analysis method to form a confidence-interval procedure. Alternatives for estimating the degrees of freedom for the procedure are investigated. The main result is an asymptotically valid confidence-interval procedure that, empirically, has good small-sample properties.
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    Annals of operations research 52 (1994), S. 107-129 
    ISSN: 1572-9338
    Keywords: DSS ; intelligent front-ends ; knowledge-based systems ; MADM ; outranking ; Scheduling ; simulation
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    Topics: Mathematics , Economics
    Notes: Abstract Knowledge-based systems (KBS) can help to make simulation available to a large group of users. We want to exemplify this by describing a decision support system (DSS) for short term rescheduling in manufacturing called SIMULEX. It couples expert systems, simulation, and a multiattribute decision making (MADM) procedure to assist the production manager. After an introduction to simulation as a problem solving tool, the current problems in production control and the goals of the project are described. Then, the various components of SIMULEX are explained in some detail. Some results and a short outlook conclude the article.
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    Discrete event dynamic systems 4 (1994), S. 87-111 
    ISSN: 1573-7594
    Keywords: Discrete event systems ; piecewise deterministic control ; manufacturing systems ; simulation ; stochastic approximation ; gradient estimation ; perturbation analysis
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    Topics: Mathematics
    Notes: Abstract This paper deals with a class of piecewise determinstic control systems for which the optimal control can be approximated through the use of an optimization-by-simulation approach. The feedback control law is restricted to belong to an a priori fixed class of feedback control laws depending on a (small) finite set of parameters. Under some general conditions developed in this paper, infinitesimal perturbation analysis (IPA) can be used to estimate the gradient of the objective function with respect to these parameters for finite horizon simulation and the consistency of the IPA estimators, as the simulation length goes to infinity, is assured. Also, the parameters can be optimized through a stochastic approximation (SA) algorithm combined with IPA. We prove that in this context, under appropriate conditions, such an approach converges towards the optimum.
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    Statistics and computing 4 (1994), S. 189-201 
    ISSN: 1573-1375
    Keywords: Markov random fields ; posterior Gibbs distributions ; simulation ; Swendsen-Wang algorithm ; Gibbs sampler ; restoration ; monitoring convergence
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    Topics: Computer Science , Mathematics
    Notes: Abstract We show in detail how the Swendsen-Wang algorithm, for simulating Potts models, may be used to simulate certain types of posterior Gibbs distribution, as a special case of Edwards and Sokal (1988), and we empirically compare the behaviour of the algorithm with that of the Gibbs sampler. Some marginal posterior mode and simulated annealing image restorations are also examined. Our results demonstrate the importance of the starting configuration. If this is inappropriate, the Swendsen-Wang method can suffer from critical slowing in moderately noise-free situations where the Gibbs sampler convergence is very fast, whereas the reverse is true when noise level is high.
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    Discrete event dynamic systems 4 (1994), S. 129-169 
    ISSN: 1573-7594
    Keywords: Transfer lines ; tandem queues ; performance analysis ; simulation
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    Topics: Mathematics
    Notes: Abstract We extend previous research on the use of models ofcontinuous tandem (CT) lines for performance analysis ofdiscrete tandem (DT) production lines. We formalize the translation of input parameters from the DT line to the CT model, as well as the translation of performance measures (PMs) obtained from the CT model back to the DT line. We show that although the CT model conceptually represents a line with continuous fluid, it can be represented as a generalized semi-Markov process (GSMP). This representation leads to a simple and concise simulation algorithm for a CT model. We investigate the accuracy of the CT model for prediction of PMs in the DT line, and show that, with proper translation of parameters and PMs, the CT model provides reasonable estimates for the DT line PMs. We provide preliminary results on gradient estimation for CT models via infinitestimal perturbation analysis. The aim of the paper is to provide a firm foundation for the future exploration of CT models as a means to parameter optimization for DT lines.
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    Annals of the Institute of Statistical Mathematics 45 (1993), S. 211-221 
    ISSN: 1572-9052
    Keywords: Approximation ; estimation variance ; pair correlation function ; Poisson process ; product density ; simulation
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    Notes: Abstract Approximations of the estimation variances of kernel estimators of the pair correlation function and the product density of a planar Poisson process are given. Furthermore, a heuristic approximation of the estimation variance of an estimator of the pair correlation function of a “general” planar point process is suggested. All formulae have been tested by simulation experiments.
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    Mathematical geology 25 (1993), S. 329-355 
    ISSN: 1573-8868
    Keywords: spatial entropy ; Gaussian model ; simulation ; fluid flow
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    Topics: Geosciences , Mathematics
    Notes: Abstract The majority of geostatistical estimation and simulation algorithms rely on a covariance model as the sole characteristic of the spatial distribution of the attribute under study. The limitation to a single covariance implicitly calls for a multivariate Gaussian model for either the attribute itself or for its normal scores transform. The Gaussian model could be justified on the basis that it is both analytically simple and it is a maximum entropy model, i.e., a model that minimizes unwarranted structural properties. As a consequence, the Gaussian model also maximizes spatial disorder (beyond the imposed covariance) which can cause flow simulation results performed on multiple stochastic images to be very similar; thus, the space of response uncertainty could be too narrow entailing a misleading sense of safety. The ability of the sole covariance to adequately describe spatial distributions for flow studies, and the assumption that maximum spatial disorder amounts to either no additional information or a safe prior hypothesis are questioned. This paper attempts to clarify the link between entropy and spatial disorder and to provide, through a detailed case study, an appreciation for the impact of entropy of prior random function models on the resulting response distributions.
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    Mathematical methods of operations research 38 (1993), S. 235-260 
    ISSN: 1432-5217
    Keywords: Boolean model ; damaged forests ; mark correlation function ; marked point process ; M/G/∞ ; random compact set ; simulation ; spatial correlation ; spatial statistics ; stochastic model ; tumor
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    Topics: Mathematics , Economics
    Notes: Abstract This paper discusses some models of stochastic geometry which are of potential interest for operations research. These are the Boolean model, a certain model for random compact sets and marked point processes. The Boolean model is a generalization of the well-known queueing systemM/G/∞. The random compact set model may be useful for modelling spatial spreading processes such as fires, cancers or holes in the Earth's surface. Marked point processes are used here as models of forests and used for a statistical study of the spatial distribution of damaged trees.
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    Statistics and computing 3 (1993), S. 27-35 
    ISSN: 1573-1375
    Keywords: elemental set ; Mahalanobis distance ; masking ; Monte Carlo testing ; normalized distance ; outliers ; simulation ; stalactite plot
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    Topics: Computer Science , Mathematics
    Notes: Abstract Detection of multiple outliers in multivariate data using Mahalanobis distances requires robust estimates of the means and covariance of the data. We obtain this by sequential construction of an outlier free subset of the data, starting from a small random subset. The stalactite plot provides a cogent summary of suspected outliers as the subset size increases. The dependence on subset size can be virtually removed by a simulation-based normalization. Combined with probability plots and resampling procedures, the stalactite plot, particularly in its normalized form, leads to identification of multivariate outliers, even in the presence of appreciable masking.
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    Annals of operations research 39 (1992), S. 157-172 
    ISSN: 1572-9338
    Keywords: Score function method ; likelihood ratio ; sensitivity analysis ; simulation ; Monte Carlo methods ; conditioning
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    Topics: Mathematics , Economics
    Notes: Abstract We consider first a discrete event static system that is to be simulated at values of a parameter or vector of parametersθ. The system is assumed driven by an inputX, where typicallyX is a vector of variables whose densityf θ (x) depends on the parameterθ. For the purpose of optimizing, finding roots, or graphing the expected performanceE θ L(X) for performance measureL, it is useful to estimate not only the expected value but also its gradient. An unbiased estimator for the latter is the score function estimator $$L(X)S(\theta ) = L(X)\frac{\partial }{{\partial \theta }}\ln f_\theta (x).$$ This estimator and likelihood ratio analogues typically require variance reduction, and we consider conditioning on the value of the score function for this purpose. The efficiency gains due to performing the Monte Carlo conditionally can be very large. Extension to discrete event dynamic systems such as theM/G/1 queue and other more complicated systems is considered.
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    Annals of operations research 39 (1992), S. 1-39 
    ISSN: 1572-9338
    Keywords: Stochastic programming ; stochastic quasigradient methods ; discrete event systems ; simulation ; concurrent approximation and optimization
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    Topics: Mathematics , Economics
    Notes: Abstract In this paper, stochastic programming techniques are adapted and further developed for applications to discrete event systems. We consider cases where the sample path of the system depends discontinuously on control parameters (e.g. modeling of failures, several competing processes), which could make the computation of estimates of the gradient difficult. Methods which use only samples of the performance criterion are developed, in particular finite differences with reduced variance and concurrent approximation and optimization algorithms. Optimization of the stationary behavior is also considered. Results of numerical experiments and convergence results are reported.
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    Mathematical geology 24 (1992), S. 99-128 
    ISSN: 1573-8868
    Keywords: correlation ; fractal functions ; fractional Brownian bridges ; hydrology ; expert input ; mining ; Monte Carlo ; nonstationary ; probability ; random walk ; reservoir engineering ; risk analysis ; sampling ; simulation ; stochastic process ; trajectory ; waste cleanup
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract This paper describes a new method of analyzing the risk incurred when the outcome of a decision depends on interpolated values, for example, on the flow through an aquifer sparsely sampled for permeability or on the ratio of waste to ore in a mineral deposit sparsely sampled for grade. The method uses large families of interpolations constructed between sample values using adaptations of the well-known midpoint displacement method for generating pseudo-fractional Brownian motion trajectories. The parameters defining each family are chosen interactively by specialists to incorporate their expert knowledge. Each family, or ensemble, then defines a population of values for any global characteristic (functional) such as flow rate or waste ratio. The probabilities of various outcomes are estimated by counting them and calculating their ratios. For example, if 900 out of 1000 are acceptable the chance of success is estimated to be 90%.
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    Mathematical methods of operations research 36 (1992), S. 477-495 
    ISSN: 1432-5217
    Keywords: Cost-oriented assembly line balancing ; heuristic algorithms ; worst-case analysis ; simulation ; NP-completeness ; time complexity
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    Topics: Mathematics , Economics
    Notes: Abstract Two new heuristic algorithms for solving cost-oriented assembly line balancing problems -the Wage-Rate-Method (WR) and the Wage-Rate-Smoothing-Method (WRS) — are presented and compared with two known heuristics — the Positional-Weight-Method (PW) and the Positional-Weight-Wage-Rate-Difference-Method (PWWD) with respect to their solution qualities. Firstly, the heuristics are outlined and their computational effort is stated. Then, a theoretical worst-case bound for the solution quality is given and the results of an extensive performance study are reported. In the study the heuristics were investigated with respect to their solution quality by solving randomly generated line balancing problems and problems from literature. It can be concluded that PWWD and WRS are generally superior to PW and WR.
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    Statistics and computing 2 (1992), S. 25-36 
    ISSN: 1573-1375
    Keywords: Reasoning under uncertainty ; causal probabilistic network ; influence diagram ; belief network ; knowledge-based systems ; evidence ; fast retraction ; maxinlization ; explanation ; simulation ; junction tree ; charge ; potential function ; flow ; propagation
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    Topics: Computer Science , Mathematics
    Notes: Abstract A probabilistic expert system provides a graphical representation of a joint probability distribution which can be used to simplify and localize calculations. Jensenet al. (1990) introduced a ‘flow-propagation’ algorithm for calculating marginal and conditional distributions in such a system. This paper analyses that algorithm in detail, and shows how it can be modified to perform other tasks, including maximization of the joint density and simultaneous ‘fast retraction’ of evidence entered on several variables.
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    OR spectrum 13 (1991), S. 159-166 
    ISSN: 1436-6304
    Keywords: Facility location for obnoxious facilities ; Gaussian model ; simulation ; Standortplanung für umweltbelastende Anlagen ; Gauß-Modell ; Simulation
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    Topics: Mathematics , Economics
    Description / Table of Contents: Zusammenfassung In dieser Arbeit werden zunächst die in neuerer Zeit entwickelten wind-diskreten Modelle und Verfahren zur Standortplanung für unerwünschte, umweltbelastende Anlagen analysiert und die Grenzen dieser Ansätze für die Lösung praktischer Problemstellungen aufgezeigt. Basierend auf diesen Erkenntnissen wird ein simulations-basiertes Verfahren für ein neues wind-stetiges Modell vorgestellt, das diese Schwachstellen überwindet. Abschließend wird das Basis-Standortmodell durch Einbeziehung der Emissionshöhe als Entscheidungsvariable erweitert.
    Notes: Summary The present paper regards the location of obnoxious facilities in the context of a realistic environment. Efforts have been made in the past towards this direction, without much success as fas as the modeling is concerned. The prevailing meteorological conditions of the area under consideration, that evidently play an important role in the dispersion of pollution, either were completely ignored or inadequately considered. In this work, the most recent wind-discrete models and solution methods are presented and analyzed and their limitations are identified. A new simulation-aided wind-continuous model is introduced capable of remedying the above limitations. Finally, a generalization is proposed and discussed, regarding the introduction of the stack height as a decision variable in the relative model.
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    Mathematical geology 23 (1991), S. 219-239 
    ISSN: 1573-8868
    Keywords: parameter estimation ; simulation ; groundwater contamination
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    Topics: Geosciences , Mathematics
    Notes: Abstract A procedure to estimate the probability of intercepting a contaminant groundwater plume for monitoring network design has been developed and demonstrated. The objective of the procedure is to use all available information in a method that accounts for the heterogeneity of the aquifer and the paucity of data. The major components of the procedure are geostatistical conditional simulation and parameter estimation that are used sequentially to generate flow paths from a suspected contaminant source location to a designated monitoring transect. From the flow paths, a histogram is constructed that represents the spatial probability distribution of plume centerlines. With an independent estimate of the plume width, a relationship between the total cost and the probability of detecting a plume can be made. The method uses geostatistical information from hydraulic head measurements and is conditioned by the data and the physics of groundwater flow. This procedure was developed specifically for the design of monitoring systems at sites where very few, if any, hydraulic conductivity data are available.
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    Journal of nondestructive evaluation 9 (1990), S. 81-99 
    ISSN: 1573-4862
    Keywords: Ultrasonics ; visualization ; simulation
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    Topics: Electrical Engineering, Measurement and Control Technology , Mathematics
    Notes: Abstract Numerical calculations have been carried out for about 20 years, and the results are demonstrated graphically by vector or lattice representations. These results are now being used mainly for clarifying the mechanisms of ultrasonic interaction with material and defects and checking and improving the experimental results. Parts of this paper review results, many involving cracktip diffraction in various geometries, which have been published mainly in conference proceedings and have not appeared in journals. Other parts, dealing with focused fields, focal lenses, and radiation in an anisotropic medium are new, and have not appeared even as conference papers.
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    Mathematical geology 22 (1990), S. 175-188 
    ISSN: 1573-8868
    Keywords: auto-correlation ; autoregressive model ; cross-correlation ; space ; simulation
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    Topics: Geosciences , Mathematics
    Notes: Abstract Analytical formulation of a general simulation model for generation of anisotropic as well as isotropic synthetic patterns in one, two, or three dimensions is proposed. It has significance for the purpose of modeling geologic properties such as ore grades, reservoir porosity, mineral distribution, fracture spacings, aperture, orientations, etc. General procedures for such a simulation by the autoregressive process are given for model parameters estimation and synthetic pattern generation. The model works on the square net basis and generates sequential patterns first along any desired direction for unidimensional simulation and then two-dimensional patterns are constructed with reference to two orthogonal unidimensional sequences. Applications to synthetic two-dimensional pattern are shown for isotropic cases with different model parameters. The extension of the model to three-dimensional space is readily available.
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    Mathematical geology 22 (1990), S. 151-173 
    ISSN: 1573-8868
    Keywords: information theory ; multidimensional normality ; profile log-likelihood ; prediction ; simulation ; statistical inference
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    Topics: Geosciences , Mathematics
    Notes: Abstract The analysis of, and from, models of spatial data usually proceeds under the assumption, often implicit, that the correct model has been specified. However, any model identification procedures based on sample data are subject to error, and consequences of such errors then permeate subsequent analysis. Thus, an attempt to quantify some of these consequences is of interest. A standard framework for analysis is extended here, by introduction of information theory, to permit the study of effects of model misspecification on maximum likelihood estimators of parameters of model covariance. Asymptotically valid theoretical results are presented, and the relevance of these results to samples of finite sizes met in practice is assessed in a series of simulation experiments. The effect of model misspecification, and use of estimators of parameters of misspecified covariance models, on the practical problem of prediction at a previously unsampled location is considered briefly, and further areas for possible investigation are outlined.
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    ISSN: 1572-9125
    Keywords: 65F10 ; Semiconductors ; simulation ; partial differential equations
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    Topics: Mathematics
    Notes: Abstract The alternate-block-factorization (ABF) method is a procedure for partially decoupling systems of elliptic partial differential equations by means of a carefully chosen change of variables. By decoupling we mean that the ABF strategy attempts to reduce intra-equation coupling in the system rather than intra-grid coupling for a single elliptic equation in the system. This has the effect of speeding convergence of commonly used iteration schemes, which use the solution of a sequence of linear elliptic PDEs as their main computational step. Algebraically, the change of variables is equivalent to a postconditioning of the original system. The results of using ABF postconditioning on some problems arising from semiconductor device simulation are discussed.
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    Acta applicandae mathematicae 14 (1989), S. 135-142 
    ISSN: 1572-9036
    Keywords: 92A07 ; immune system ; modelling ; simulation
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    Topics: Mathematics
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    Acta applicandae mathematicae 14 (1989), S. 179-189 
    ISSN: 1572-9036
    Keywords: 92A07 ; immune response ; ordinary differential equations ; simulation
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    Topics: Mathematics
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    ISSN: 1572-9036
    Keywords: 92A07 ; immune response ; metabolism ; simulation
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    Mathematical programming 42 (1988), S. 53-68 
    ISSN: 1436-4646
    Keywords: Design of experiments ; normal random variates ; pseudorandom ; simulation ; statistical inference
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    Topics: Computer Science , Mathematics
    Notes: Abstract More and more problems are being tackled by simulation as large computing costs per hour approach those of mathematicians' time. Abuses of simulation arise from ignorance or careless use of little understood procedures, and some of the fundamental tools of the subject are much less well understood than commonly supposed. This is illustrated here by the saga of pseudorandom number generators, normal variate generators and the analysis of queueing system simulations. On the positive side, genuinely new uses of simulation are appearing, particularly in statistical inference. These are exemplified by recursive algorithms for simulating complex systems and simulation-based likelihood inference for point processes.
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    Annals of operations research 15 (1988), S. 269-287 
    ISSN: 1572-9338
    Keywords: Production scheduling ; integer programming ; simulation ; flexible manufacturing ; hierarchical modelling
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    Topics: Mathematics , Economics
    Notes: Abstract This study reports the development of a production scheduling system for the integrated management of production in large-scale, high-volume electronic assembly lines. The development of the system incorporates control and planning considerations by addressing the interaction of various subsystems. Stochastic and deterministic aspects of the problem environment are appropriately handled via relevant simulation and analytic models. By effecting a hierarchical breakdown of the problem environment, the system produces information used in practical decision making for production planning and scheduling. Procedures used encompass and address considerations for management of work-in-process, optimization of the various subsystems' performance, minimization of setup time effect, and inventory carrying costs.
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    Annals of operations research 15 (1988), S. 227-267 
    ISSN: 1572-9338
    Keywords: FMS ; production ratios ; mathematical programming ; levels of detail in modeling ; balanced machine workloads ; machine utilizations ; dispatching rules ; simulation
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    Topics: Mathematics , Economics
    Notes: Abstract Stecke [21] has developed mathematical programming approaches for determining, from a set of part type requirements, the production ratios (part types to be produced next, and their proportions) which maximize overall machine utilizations by balancing machine workloads in a flexible manufacturing system (FMS). These mathematical programming (MP) approaches are aggregate in the sense that they do not take into account such things as contention for transportation resources, travel time for work-in-process, contention for machines, finite buffer space, and dispatching rules. In the current study, the sensitivity of machine utilizations to these aggregations is investigated through simulation modeling. For the situation examined, it is found that achieved machine utilizations are a strong function of some of the factors ignored in the MP methodology, ranging from 9.1% to 22.9% less than those theoretically attainable under the mathematical programming assumptions. The 9.1% degradation results from modeling with nonzero work-in-process travel times (i.e. 2 minutes per transfer) and using only central work-in-process buffers. Resource levels (e.g. the number of automated guided vehicles; the amount of work-in-process; the number of slack buffers) needed to limit the degradation to 9.1% correspond to FMS operating conditions which are feasible in practice.
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    BIT 28 (1988), S. 671-677 
    ISSN: 1572-9125
    Keywords: I.6.1 ; I.6.3 ; simulation ; Bernoulli ; binomial ; uniform sums ; 0–1 arrays
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    Topics: Mathematics
    Notes: Abstract Sums of independent, identically distributed (iid) binomial variates have binomial distributions; yet it is possible to construct a sequence of binomial distributions over {0, 1} for variatesX 1,X 2, ... such that all partial sumsY i =X 1 + ... +X i have uniform distributions. The price to pay is to give up the iid condition. Requiring the property of only one sum does not alleviate the situation much. It is also possible to generate on a computerm × n-matrices, of 0–1 binomial variates with uniformly distributed row and column sums of all major submatrices, but only for smallm andn. Even a three-dimensional 2 × 2 × 2 array can have a similar property. Other target distributions than the rectangular are possible, but cumbersome. An example with smaller variance is given. The results were needed for simulating the performance of some Operations Research algorithms.
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    ISSN: 1436-4646
    Keywords: 90C27 ; 68Q10 ; 68R05 ; Parallel computer ; MIMD ; branch and bound ; nondeterminism ; asynchronicity ; simulation
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    Topics: Computer Science , Mathematics
    Notes: Abstract Parallel computation offers a challenging opportunity to speed up the time consuming enumerative procedures that are necessary to solve hard combinatorial problems. Theoretical analysis of such a parallel branch and bound algorithm is very hard and empirical analysis is not straightforward because the performance of a parallel algorithm cannot be evaluated simply by executing the algorithm on a few parallel systems. Among the difficulties encountered are the noise produced by other users on the system, the limited variation in parallelism (the number of processors in the system is strictly bounded) and the waste of resources involved: most of the time, the outcomes of all computations are already known and the only issue of interest is when these outcomes are produced. We will describe a way to simulate the execution of parallel branch and bound algorithms on arbitrary parallel systems in such a way that the memory and cpu requirements are very reasonable. The use of simulation has only minor consequences for the formulation of the algorithm.
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    Mathematical programming 42 (1988), S. 33-40 
    ISSN: 1436-4646
    Keywords: Decision theory ; mathematical modelling ; operational research ; simulation
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    Acta applicandae mathematicae 11 (1988), S. 1-17 
    ISSN: 1572-9036
    Keywords: 92 (30E) ; Psychophysics ; sensory noise ; chaos ; feedforward processes ; simulation ; nonlinear modelling
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    Topics: Mathematics
    Notes: Abstract A cubic recursion with complex variable, has different properties in the phase spases of the reals and the imaginaries. The separation of the dynamics of the parts may be interpretable in terms of sensory intensity signal transmission through higher neural networks in man.
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    Annals of operations research 8 (1987), S. 363-381 
    ISSN: 1572-9338
    Keywords: Probability ; simulation ; petroleum ; resources ; appraisal
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    Topics: Mathematics , Economics
    Notes: Abstract An analytic probabilistic methodology for resource appraisal of undiscovered oil and gas resources in play analysis is presented. This play-analysis methodology is a geostochastic system for petroleum resource appraisal in explored as well as frontier areas. An objective was to replace an existing Monte Carlo simulation method in order to increase the efficiency of the appraisal process. Underlying the two methods is a single geologic model which considers both the uncertainty of the presence of the assessed hydrocarbon and its amount if present. The results of the model are resource estimates of crude oil, nonassociated gas, dissolved gas, and gas for a geologic play in terms of probability distributions. The analytic method is based upon conditional probability theory and a closed form solution of all means and standard deviations, along with the probabilities of occurrence.
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    Annals of operations research 8 (1987), S. 243-256 
    ISSN: 1572-9338
    Keywords: Control variates ; Monte Carlo ; nonlinear estimation ; simulation ; variance reduction
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    Topics: Mathematics , Economics
    Notes: Abstract The sampling distribution of parameter estimators can be summarized by moments, fractiles or quantiles. For nonlinear models, these quantities are often approximated by power series, approximated by transformed systems, or estimated by Monte Carlo sampling. A control variate approach based on a linear approximation of the nonlinear model is introduced here to reduce the Monte Carlo sampling necessary to achieve a given accuracy. The particular linear approximation chosen has several advantages: its moments and other properties are known, it is easy to implement, and there is a correspondence to asymptotic results that permits assessment of control variate effectiveness prior to sampling via measures of nonlinearity. Empirical results for several nonlinear problems are presented.
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    Annals of operations research 8 (1987), S. 351-362 
    ISSN: 1572-9338
    Keywords: Response surface methodology ; simulation ; optimization
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    Topics: Mathematics , Economics
    Notes: Abstract Managing the volume of experimental and/or simulation data required for large-scale design studies can be a significant problem. This paper describes a method for dealing with this problem, using response surface methodology. The method involves (1) determining a summary parameterization of the response of the underlying process mechanism generating the data, in order to characterize this response in terms of a manageable set of performance measures, and (2) deriving a model of the data, in order to summarize the dependence of the performance measures on selected predictor or design variables. The method is illustrated by its application to a problem in vehicle collision research.
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    Mathematical geology 19 (1987), S. 99-107 
    ISSN: 1573-8868
    Keywords: geostatistics ; simulation ; Toeplitz matrices ; block Toeplitz matrices ; matrix polynomial approximation
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    Topics: Geosciences , Mathematics
    Notes: Abstract An algorithm for producing a nonconditional simulation by multiplying the square root of the covariance matrix by a random vector is described. First, the square root of a matrix (or a function of a matrix in general) is defined. The square root of the matrix can be approximated by a minimax matrix polynomial. The block Toeplitz structure of the covariance matrix is used to minimize storage. Finally, multiplication of the block Toeplitz matrix by the random vector can be evaluated as a convolution using the fast Fourier transform. This results in an algorithm which is not only efficient in terms of storage and computation but also easy to implement.
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    Annals of operations research 3 (1985), S. 355-377 
    ISSN: 1572-9338
    Keywords: Flexible manufacturing systems ; scheduling ; manufacturing systems ; simulation ; computer integrated manufacturing
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    Topics: Mathematics , Economics
    Notes: Abstract This paper presents a new two-phase (TP) approximate method for real-time scheduling in a flexible manufacturing system (FMS). This method combines a reduced enumeration schedule generation algorithm with a 0–1 optimization algorithm. In order to make the combined algorithm practicable, heuristic rules are introduced for the selection of jobs to be scheduled. The relative performance of the TP method vis-a-vis conventional heuristic dispatching rules such as SPT, LPT, FCFS, MWKR, and LWKR is investigated using combined process-interaction/discrete-event simulation models. An efficient experimental procedure is designed and implemented using these models, and the statistical analysis of the results is presented. For the particular case investigated, the conclusions are very encouraging. In terms of mean flow time, the TP method performs significantly better than any other tested heuristic dispatching rules. Also, the experimental results show that using global information significantly improves the FMS performance.
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    Annals of operations research 3 (1985), S. 13-21 
    ISSN: 1572-9338
    Keywords: Flexible manufacturing systems ; queueing models ; simulation ; performance evaluation
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    Topics: Mathematics , Economics
    Notes: Abstract Flexible manufacturing systems (FMSs) are a class of automated systems which can be used to improve productivity in discrete parts manufacturing. Due to the complexity of these systems, it is useful to have models that can aid in the design and operation of FMSs. We specifically differentiate here betweengenerative (or prescriptive) models, whichfind candidate decisions, andevaluative (or descriptive) models, whichevaluate a given set of decisions. We briefly cover, in a practical context, the pros and cons of these two classes of models. Then we focus on the latter class of models. Evaluative models for FMSs fall into five main classes, based on the technique used, namely: static allocation, queueing network theory, simulation, perturbation analysis, and Petri nets. Each of these approaches is briefly described, advantages and disadvantages mentioned, and references given to more detailed papers.
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    Annals of operations research 3 (1985), S. 379-391 
    ISSN: 1572-9338
    Keywords: Flexible manufacturing systems ; discrete event systems ; real-time systems ; monitoring ; simulation ; performance evaluation ; perturbation analysis
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    Topics: Mathematics , Economics
    Notes: Abstract The recent perturbation analysis approach to discrete event systems is applied to flexible manufacturing systems (FMS). While analytic (queueing) models are useful in preliminary design of such systems, they are not accurate enough at the detailed design/operation stage. Thus, experimentation on detailed simulations or on the actual system has been the way to optimize system performance. Perturbation analysis allows us to derive the sensitivity of system performance, with respect to several design/operating parameters, by observing a single experiment (and without having to actually alter the parameters — often a costly operation). Thus, observation of one experiment can give accurate directions for the improvement of several parameter values. Here we give a simulation example illustrating how perturbation analysis could be used on-line on an FMS to improve its performance, including reducing its operating cost. Experimental results are also presented validating the estimates obtained from this technique.
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    Mathematical geology 17 (1985), S. 41-52 
    ISSN: 1573-8868
    Keywords: fracture set ; simulation ; spectral density ; Fourier transform
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract Fracture set properties such as orientation, spacing, trace length, and waviness tend to be spatially correlated. These properties can be efficiently simulated by spectral analysis procedures that take advantage of the computational speed of the fast Fourier transform. The covariance function of each property to be simulated is obtained from the variogram function estimated from mapped fracture set data and is typically referenced to the mean vector of the set. Simulation procedures for normally and exponentially distributed data involve generating uncorrelated Fourier coefficients that are assigned proper variance according to the spectral density, which is the Fourier transform of the covariance function. These coefficients are then reverse Fourier transformed to produce simulated set properties that have the desired variance and variogram function.
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    Mathematical geology 17 (1985), S. 81-90 
    ISSN: 1573-8868
    Keywords: simulation ; turning bands ; covariance ; semivariogram ; geostatistics
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    Topics: Geosciences , Mathematics
    Notes: Abstract Journel (1974) developed the turning-bands method which allows a three-dimensional data set with specified covariance to be obtained by the simulation of several one-dimensional realizations which have an intermediate covariance. The relationship between the threedimensional and one-dimensional covariance is straightforward and allows the one-dimensional covariance to be obtained immediately. In theory a dense uniform distribution of lines in three-dimensional space is required along which the one-dimensional realizations are generated; in practice most workers have been content to use the fifteen axes of the regular icosahedron. Many mining problems may be treated in two dimensions, and in this paper a turning-bands approach is developed to generate two-dimensional data sets with a specified covariance. By working in two dimensions, the area on which the data is simulated may be divided as finely as desired by the lines on which the one-dimensional realizations are first generated. The relationship between the two-dimensional and one-dimensional covariance is derived as a nontrivial integral equation. This is solved analytically for the onedimensional covariance. The method is applied to the generation of a two-dimensional data set with spherical covariance.
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    Mathematical geology 17 (1985), S. 625-644 
    ISSN: 1573-8868
    Keywords: recoveries ; multi-Gaussian ; bi-Gaussian ; simulation ; disjunctive kriging
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    Topics: Geosciences , Mathematics
    Notes: Abstract A new and simple method is proposed to obtain estimates of recovery functions: the Bi-Gaussian approach. Existing methods estimate recovery functions with conditional distributions where the conditioning set is all the data available. Here instead the simple kriging estimate of the Gaussian transform is proposed to be used. Results in the point recovery case are identical to the multi-Gaussian approach of Verly (1983, 1984), whereas in the non-point-support situation, an approximation is derived which saves computer time as compared to employing the strict multi-Gaussian hypothesis. Two examples compare favorably with the well-established disjunctive kriging method (discrete Gaussian model).
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  • 89
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    Mathematical geology 16 (1984), S. 449-463 
    ISSN: 1573-8868
    Keywords: autorun function ; groundwater ; porosity ; random field ; simulation ; specific surface
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract Fundamentals of autorun analysis have been given to describe porous media geometry, including sedimantary rocks. The mathematical abstraction of porous media has been presented on the basis of random fields. Classical parameters of porous media, such as porosity and specific surface, have been expressed in terms of autorun function. Finally, a stochastic model has been proposed for the underlying generating mechanism of the porous medium. This model is capable of producing synthetic porous medium and, on the average, porosity as well as the specific surface. The first autorun coefficient is asymptotically equal to the porosity of the medium concerned. It also has been observed that the porosity together with the autorun function are sufficient to produce the specific surface value of the medium.
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    Journal of optimization theory and applications 40 (1983), S. 625-630 
    ISSN: 1573-2878
    Keywords: Discrete event systems ; Monte Carlo methods ; stochastic processes ; queueing theory ; simulation ; perturbation analysis ; sensitivity analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A new approach to the optimization of discrete-event dynamic systems has recently been developed (Refs. 1–4). The implementation of this approach requires answering the following question: given an observed value of the outcome of a random variable, what would have been the outcome if the parameters of the random variable had been different? The answer to this question would traditionally involve the value of an outcome in an underlying sample space. However, this underlying value cannot normally be observed. In this note, we give a framework for answering this question, in terms of the observed value alone. This point had not been considered rigorously in the new approach of Refs. 1–4, and our note derives a basic equation required for that approach.
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    Mathematical geology 14 (1982), S. 445-456 
    ISSN: 1573-8868
    Keywords: semivariogram ; simulation ; autoregressive process ; serial correlation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract The semivariogram obtained from simulated space series formed by an autoregressive (AR) process gives a ready explanation for most of the common types. Linear semivariograms arise from a random walk (Brownian motion) process while the transitive and exponential types are generated by an AR process of first order. The continuous (“Gaussian”) type arises from a process of second order which also accounts for the “hole-effect” when the process becomes pseudo-periodic. The nugget effect can be included by the addition of a moving average (MA) process of first order.
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    Mathematical geology 12 (1980), S. 25-32 
    ISSN: 1573-8868
    Keywords: random function ; geostatistics ; simulation ; covariance
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    Topics: Geosciences , Mathematics
    Notes: Abstract This paper presents a new geostatistical method to obtain realizations of stationary random functions in the plane.
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    BIT 18 (1978), S. 320-333 
    ISSN: 1572-9125
    Keywords: Priority queues ; simulation ; event chains ; index organization ; p-trees ; 3.74 ; 4.34 ; 4.6 ; 8.1
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Two priority queue algorithms, a linked linear sublist and ap-subtree algorithm, are analysed. Both of them use a search index that speeds up finding the correct sublist/subtree. In most cases the methods require a short processing time for the so-called HOLD-operation of the discrete event simulation. The relative power of the algorithms depends on the ratior of the total number of elements in the queue and the size of the search index. For large values ofr (≧16) thep-subtree algorithm is to be preferred. However, the more primitive data structure used by the sublist algorithm makes it possible to use a larger index leading to a smaller ratior.
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    Mathematical geology 9 (1977), S. 497-506 
    ISSN: 1573-8868
    Keywords: principal components ; sampling ; simulation
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    Topics: Geosciences , Mathematics
    Notes: Abstract The convenience of reducing the dimension of a data matrix by principal component analysis invites substantive interpretation of the coefficients of the components. To test the consistency of component coefficients, 10 samples of approximately 25, 50, 100, and 200 items each were randomly drawn, with replacement, from a source sample consisting of 2086 subalkaline asalt analyses. From each sample principal components were calculated using 9 major oxides as variables. Although the eigenvalues are remarkably consistent, both across and within sample size groups, the coefficients of the eigenvectors are subject to considerable sample variance. It is sometimes assumed that the coefficients of the components calculated from small samples are well enough known to be used in detailed petrological interpretation. Our results indicate that the validity of this assumption should be tested in each specific research even when rather large samples are used. The testing procedure used here is suitable of a sufficiently large reservoir of sample items is available; in the absence of such a reservoir complete simulation could be used.
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    Mathematical geology 8 (1976), S. 43-56 
    ISSN: 1573-8868
    Keywords: finite-element method ; numerical analysis ; simulation ; geophysics ; groundwater
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    Topics: Geosciences , Mathematics
    Notes: Abstract Deterministic mathematical modeling of complex geologic transport processes may require the use of odd boundary shapes, time dependency, and two or three dimensions. Under these circumstances the governing transport equations must be solved by numerical methods. For a number of transport phenomena a general form of the convective-dispersion equation can be employed. The solution of this equation for complicated problems can be solved readily by the finite-element method. Using quadrilateral isoparametric elements or triangular elements and a computational algorithm based on Galerkin's procedure, solutions to unsteady heat flux from a dike and seawater intrusion in an aquifer have been obtained. These examples illustrate that the finite-element numerical procedure is well suited for solving boundary-value problems resulting from modeling of complex physical phenomena.
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    Mathematical geology 8 (1976), S. 37-42 
    ISSN: 1573-8868
    Keywords: simulation ; null correlations ; null model and Pearson correlation ; power oft″-test
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    Topics: Geosciences , Mathematics
    Notes: Abstract Chayes' t″-test for closure correlations is developed from various approximations and assumptions. The empirical behavior of this test is observed through the use of random-sampling number matrices of order to thirteen. The experiments demonstrate a lower limit for the reliability of Chayes' model of about 91/100. That is, about one chance in ten remains that an error due to the statistical testing is committed on some product-moment correlations in a given matrix of correlation, given a confidence level of 90 percent. With increase in the number of variables, the test for departure from zero correlation can be used provided the sample size remains small.
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    Mathematical geology 8 (1976), S. 219-242 
    ISSN: 1573-8868
    Keywords: analog computer ; simulation ; geochemistry ; phosphorus ; phosphate deposits
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract Present ionic concentrations of Ca ++,HCO 3 - ,and HPO 4 = in surface and groundwater runoff in Florida indicate that phosphorus is being concentrated in rock through dissolution and reprecipitation, with calcium phosphate increasing at the expense of calcium carbonate. Analog computer simulation of a systems model of this process suggests that significant enrichment can occur in 20 million years. The degree of enrichment depends on the supply of new phosphorus to Florida through rain and oceanic exchange processes. If the calcium phosphate content of original rock is 0.5 to 1.0 percent (0.52 to 1.05 percent P 2 O 5),a formation with 10 to 20 percent calcium phosphate (CaPO 4 or 10.5 to 21.0 percent P 2 O 5)as in the Hawthorn Formation (Miocene)may result. Nutrient upwelling along the continental slope coupled with transport to the estuaries by lateral eddy diffusion can supply an additional 400 mg P|m 2 |yr which, if deposited, would result in a sediment with a 4.3 percent CaPO 4 (4.5 percent P 2 O 5)content. If this is enriched later by resolution, 40 percent CaPO 4 (42 percent P 2 O 5)results. Through geologic time, the ocean may be considered as a source of phosphorus to the land through rain or estuarine sediment.
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    Mathematical geology 7 (1975), S. 117-128 
    ISSN: 1573-8868
    Keywords: data processing ; lognormal theory ; sampling ; simulation ; statistics ; transformations ; economic geology ; mining ; sedimentology
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract A logarithmic transformation may be used to improve the efficiency of estimates of the mean when observations follow the lognormal distribution. But if this transformation is applied to observations that follow another distribution, bias may be introduced. We consider some consequences of erroneously applying lognormal estimation theory and demonstrate that biased estimates may be obtained for certain classes of distributions. Illustrations of bias obtained in gold sampling are given.
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    Mathematical geology 7 (1975), S. 47-61 
    ISSN: 1573-8868
    Keywords: Markov processes ; simulation ; cyclothems ; stratigraphy
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract The Banff Formation (Mississippian) is a sequence of limestone and shale exposed in the southern Canadian Rocky Mountains and underlying the adjacent plains. It was chosen as a vehicle to evaluate Markov-inspired techniques in sedimentary sequences where repetition of rock types is typical but a pattern of cyclicity is not obvious. Distributions of rock-unit thickness in two outcrop sections of the Banff Formation are not all exponential, therefore a one-step Markov model using an equal observational interval is not valid. Memory is indicated by the embedded-chain model. The most likely pattern of recurrence is delineated; shale is the most independent lithologic type and therefore the initial lithology in any ideal pattern. Neither factoring nor powering a probability matrix for the Banff Formation revealed geological cyclicity as defined by W. Schwarzacher. Several problems limit the application of Markov models to sedimentary sequences. Statistical validity requires a minimum number of observations, and in the attainment of a sound statistical basis, geological pertinence may be seriously reduced. Treatment of the probability matrix, by principal components analysis or by powering, yields an exacting criterion for cyclicity.
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    ISSN: 1573-8868
    Keywords: data processing ; discriminant analysis ; graphics ; mapping ; sampling ; simulation ; geochemistry
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract The exploration geochemist faces a serious problem in reconciling theoretical statistics with the empirical distribution of elements in materials in the earth's crust. The results of computer-simulation experiments being conducted by the Exploration Geochemistry Group at the University of New Brunswick illustrate some of the problems of the relation between frequency distributions and spatial distributions of elements and raise some interesting questions about sampling patterns and physical size of samples. Most importantly, the simulation experiments and empirical examples support the contention that attempts to make an assumption of normality more efficient by performing log transformations on positively skewed data may defeat the purpose of statistical analysis for exploration work. New developments in computer-data presentation and interpretation, including population sorting and classification, illustrate the increasing use of the computer in exploration geochemistry.
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