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  • Articles  (2)
  • autoregressive process  (2)
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  • Articles  (2)
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  • Springer  (2)
  • American Geophysical Union
  • American Meteorological Society
  • American Physical Society (APS)
  • Cambridge University Press
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  • 2000-2004
  • 1980-1984  (2)
  • 1955-1959
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  • 1982  (2)
  • 1956
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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    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.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Mathematical geology 14 (1982), S. 457-474 
    ISSN: 1573-8868
    Keywords: semivariograms ; autoregressive process ; maximum entropy method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract A wide variety of semivariograms may be represented in terms of a first- or second-order autoregressive (AR) process, and the nugget effect may be included by use of a moving average (MA) process. The weighting parameters for these models have a simple functional dependence on the value of the sill and the semivariance at the first and second lag. These may be estimated either graphically from the semivariogram or directly from the computed values. Improved spectral estimates of geophysical data have been obtained by the use of the “maximum entropy method,” and the necessary equations were adapted here for the estimation of the weighting parameters of the AR and the MA processes. Comparison among the semivariograms obtained for the ideal case, the observed case, and the estimated case for artificial series show excellent correspondence between the ideal and estimated while the observed semivariogram may show marked divergence.
    Type of Medium: Electronic Resource
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