scholarly journals Bootstrapped models for intrinsic random functions

1988 ◽  
Vol 20 (6) ◽  
pp. 699-715 ◽  
Author(s):  
Katherine Campbell
Keyword(s):  
Random Functions ◽  
Intrinsic Random Functions

scholarly journals Intrinsic random functions and universal kriging on the circle

2016 ◽  
Vol 108 ◽  
pp. 33-39 ◽  
Author(s):  
Chunfeng Huang ◽  
Haimeng Zhang ◽  
Scott M. Robeson
Keyword(s):  
Universal Kriging ◽  
Random Functions ◽  
Intrinsic Random Functions

The intrinsic random functions and their applications

1973 ◽  
Vol 5 (03) ◽  
pp. 439-468 ◽  
Author(s):  
G. Matheron
Keyword(s):  
Statistical Inference ◽  
Realization Theory ◽  
Practical Applications ◽  
Random Functions ◽  
Stationary Increments ◽  
Turning Bands ◽  
Generalized Covariance ◽  
Intrinsic Random Functions ◽  
Generalized Processes ◽  
Unique Realization

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.

scholarly journals Intrinsic random functions on the sphere

2019 ◽  
Vol 146 ◽  
pp. 7-14 ◽  
Author(s):  
Chunfeng Huang ◽  
Haimeng Zhang ◽  
Scott M. Robeson ◽  
Jacob Shields
Keyword(s):  
Random Functions ◽  
Intrinsic Random Functions

scholarly journals The intrinsic random functions and their applications

1973 ◽  
Vol 5 (3) ◽  
pp. 439-468 ◽  
Author(s):  
G. Matheron
Keyword(s):  
Statistical Inference ◽  
Realization Theory ◽  
Practical Applications ◽  
Random Functions ◽  
Stationary Increments ◽  
Turning Bands ◽  
Generalized Covariance ◽  
Intrinsic Random Functions ◽  
Generalized Processes ◽  
Unique Realization

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.

scholarly journals On a class of space–time intrinsic random functions

Bernoulli ◽  
2013 ◽  
Vol 19 (2) ◽  
pp. 387-408 ◽  
Author(s):  
Michael L. Stein
Keyword(s):  
Space Time ◽  
Random Functions ◽  
Intrinsic Random Functions

Multivariate Intrinsic Random Functions for Cokriging

2009 ◽  
Vol 41 (8) ◽  
pp. 887-904 ◽  
Author(s):  
Chunfeng Huang ◽  
Yonggang Yao ◽  
Noel Cressie ◽  
Tailen Hsing
Keyword(s):  
Random Functions ◽  
Intrinsic Random Functions
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