Random set modelling of three-dimensional objects in a hierarchical Bayesian context

DOI10.1080/00949655.2012.696647zbMath1453.62157OpenAlexW2051147253MaRDI QIDQ5219210

David R. Larsen, Christopher K. Wikle, Athanasios C. Micheas

Publication date: 9 March 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2012.696647

zbMATH Keywords

mixture modelshierarchical Bayesian modelsrandom objectsbirth-death Markov chain Monte Carlodata-augmentation forestryLIDAR data

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (4)

Cox Point Processes: Why One Realisation Is Not Enough ⋮ Hierarchical Bayesian modeling of marked non-homogeneous Poisson processes with finite mixtures and inclusion of covariate information ⋮ sppmix: Poisson point process modeling using normal mixture models ⋮ Modelling the evolution of a random set utilizing covariate information with applications to nowcasting

Uses Software

• BayesDA

Cites Work

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