Conditional simulation of categorical spatial variables using Gibbs sampling of a truncated multivariate normal distribution subject to linear inequality constraints

This paper introduces a method to generate conditional categorical simulations, given an ensemble of partially conditioned (or unconditional) categorical simulations derived from any simulation process. The proposed conditioning method relies on implicit functions (signed distance functions) for rep...

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Vydané v:	Stochastic environmental research and risk assessment Ročník 35; číslo 2; s. 457 - 480
Hlavní autori:	Fouedjio, Francky, Scheidt, Celine, Yang, Liang, Wang, Yizheng, Caers, Jef
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2021 Springer Nature B.V
Predmet:	Aquatic Pollution Chemistry and Earth Sciences Computational Intelligence Computer Science Conditioning Earth and Environmental Science Earth Sciences Environment Inequality Linear functions Math. Appl. in Environmental Science Normal distribution Original Paper Physics Principal components analysis Probability Theory and Stochastic Processes Sampling Simulation Statistics for Engineering Waste Water Technology Water Management Water Pollution Control Gibbs sampler Conditional simulation Categorical spatial variable Implicit function Principal component analysis
ISSN:	1436-3240, 1436-3259
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