Modelling species abundance in a river by negative binomial hidden Markov models

DOI10.1016/j.csda.2013.09.017zbMath1471.62191OpenAlexW2066950201WikidataQ57616140 ScholiaQ57616140MaRDI QIDQ1621340

M. J. Brewer, D. Donnelly, S. L. Cooksley, A. Tree, Luigi Spezia

Publication date: 8 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2013.09.017

zbMATH Keywords

Bayesian inferencevariable selectionnon-homogeneous Markov chain\textit{Margaritifera margaritifera}river dee

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05)

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Bayesian variable selection in non-homogeneous hidden Markov models through an evolutionary Monte Carlo method

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