scholarly journals Simulating space-time random fields with nonseparable Gneiting-type covariance functions

2020 ◽  
Vol 30 (5) ◽  
pp. 1479-1495
Author(s):  
Denis Allard ◽  
Xavier Emery ◽  
Céline Lacaux ◽  
Christian Lantuéjoul
Keyword(s):  
Random Fields ◽  
Space Time ◽  
Covariance Functions

scholarly journals MODELS OF COVARIANCE FUNCTIONS OF GAUSSIAN RANDOM FIELDS ESCAPING FROM ISOTROPY, STATIONARITY AND NON NEGATIVITY

2014 ◽  
Vol 33 (1) ◽  
pp. 75
Author(s):  
Pablo Gregori ◽  
Emilio Porcu ◽  
Jorge Mateu
Keyword(s):  
Image Analysis ◽  
Random Fields ◽  
Fourier Transforms ◽  
Gaussian Random Fields ◽  
Space Time ◽  
Linear Combinations ◽  
Covariance Functions ◽  
Recent Advances ◽  
Special Cases ◽  
Covariance Models

This paper represents a survey of recent advances in modeling of space or space-time Gaussian Random Fields (GRF), tools of Geostatistics at hand for the understanding of special cases of noise in image analysis. They can be used when stationarity or isotropy are unrealistic assumptions, or even when negative covariance between some couples of locations are evident. We show some strategies in order to escape from these restrictions, on the basis of rich classes of well known stationary or isotropic non negative covariance models, and through suitable operations, like linear combinations, generalized means, or with particular Fourier transforms.

Matérn Cross-Covariance Functions for Multivariate Random Fields

2010 ◽  
Vol 105 (491) ◽  
pp. 1167-1177 ◽  
Author(s):  
Tilmann Gneiting ◽  
William Kleiber ◽  
Martin Schlather
Keyword(s):  
Random Fields ◽  
Covariance Functions ◽  
Cross Covariance
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