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  • Key words: Linex loss function  (1)
  • Lévy processes  (1)
  • 2000-2004  (2)
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  • 2000-2004  (2)
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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Journal of theoretical probability 13 (2000), S. 951-976 
    ISSN: 1572-9230
    Keywords: time-space harmonic polynomials ; Lévy processes ; Semi-stable Markov processes ; Hochberg's measure
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A time-space harmonic polynomial for a stochastic process M=(M t) is a polynomial P in two variables such that P(t, M t) is a martingale. In this paper, we investigate conditions for the existence of such polynomials of each degree in the second, “space,” argument. We also describe various properties a sequence of time-space harmonic polynomials may possess and the interaction of these properties with distributional properties of the underlying process. Thus, continuous-time conterparts to the results of Goswami and Sengupta,(2) where the analoguous problem in discrete time was considered, are derived. A few additional properties are also considered. The resulting properties of the process include independent increments, stationary independent increments and semi-stability. Finally, a generalization to a “measure” proposed by Hochberg(3) on path space is obtained.
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1435-926X
    Keywords: Key words: Linex loss function ; bounded risk estimation ; fixed-width interval estimation ; shrinkage estimator ; asymptotic second-order expansion ; three-stage ; accelerated and purely sequential stopping rules
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract. The problem of estimating a linear function of k normal means with unknown variances is considered under an asymmetric loss function such that the associated risk is bounded from above by a known quantity. In the absence of a fixed sample size rule, sequential stopping rules satisfying a general set of assumptions are considered. Two estimators are proposed and second-order asymptotic expansions of their risk functions are derived. It is shown that the usual estimator, namely the linear function of the sample means, is asymptotically inadmissible, being dominated by a shrinkage-type estimator. An example illustrates the use of different multistage sampling schemes and provides asymptotic expansions of the risk functions.
    Type of Medium: Electronic Resource
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