A comparative study of nonlinear Markov chain models for conditional simulation of multinomial classes from regular samples

DOI10.1007/S00477-007-0109-2zbMath1365.86027OpenAlexW2049448595WikidataQ57040064 ScholiaQ57040064MaRDI QIDQ954670

Chuanrong Zhang, Weidong Li

Publication date: 17 November 2008

Published in: Stochastic Environmental Research and Risk Assessment (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00477-007-0109-2

zbMATH Keywords

conditional simulationcategorical variableinterclass relationshipMarkov chain random fieldtransiogram

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Geostatistics (86A32)

Related Items (3)

Estimating threshold-exceeding probability maps of environmental variables with Markov chain random fields ⋮ Stochastic inverse method for estimation of geostatistical representation of hydrogeologic stratigraphy using borehole logs and pressure observations ⋮ Sampling strategies for uncertainty reduction in categorical random fields: formulation, mathematical analysis and application to multiple-point simulations

Uses Software

• GSLIB

Cites Work

• Unnamed Item
• Markov chain random fields for estimation of categorical variables
• Spatial prediction of categorical variables: the Bayesian maximum entropy approach
• A Markov chain model for subsurface characterization: Theory and applications
• A Bayesian/maximum-entropy view to the spatial estimation problem
• Transition probability-based indicator geostatistics

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