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The intrinsic random functions and their applications

Published online by Cambridge University Press:  01 July 2016

G. Matheron
G. Matheron*
Affiliation:
Centre de Morphologie Mathématique, Fontainebleau
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Abstract

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The intrinsic random functions (IRF) are a particular case of the Guelfand generalized processes with stationary increments. They constitute a much wider class than the stationary RF, and are used in practical applications for representing non-stationary phenomena. The most important topics are: existence of a generalized covariance (GC) for which statistical inference is possible from a unique realization; theory of the best linear intrinsic estimator (BLIE) used for contouring and estimating problems; the turning bands method for simulating IRF; and the models with polynomial GC, for which statistical inference may be performed by automatic procedures.

Keywords

GUELFAND GENERALIZED STOCHASTIC PROCESSINTRINSIC RANDOM FUNCTIONGENERALIZED COVARIANCESPOLYNOMIAL COVARIANCETURNING BANDS METHOD

Information

Type
Research Article
Information
Advances in Applied Probability , Volume 5 , Issue 3 , December 1973 , pp. 439 - 468
Copyright
Copyright © Applied Probability Trust 1973 

References

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