Bayesian model selection: The steepest mountain to climb

Autor: Iris E. Hendriks, Robert Bob O'Hara, Giacomo Tavecchia, Simone Tenan

Publikováno v: Digital.CSIC. Repositorio Institucional del CSIC
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Ecological modelling 283 (2014): 62–69. doi:10.1016/j.ecolmodel.2014.03.017
info:cnr-pdr/source/autori:Tenan, Simone; O'Hara, Robert B.; Hendriks, Iris; Tavecchia, Giacomo/titolo:Bayesian model selection: The steepest mountain to climb/doi:10.1016%2Fj.ecolmodel.2014.03.017/rivista:Ecological modelling/anno:2014/pagina_da:62/pagina_a:69/intervallo_pagine:62–69/volume:283

Following the advent of MCMC engines Bayesian hierarchical models are becoming increasingly common for modelling ecological data. However, the great enthusiasm for model fitting has not yet encompassed the selection of competing models, despite its f

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbdfa5d9e9edd9076c1c1402b99bfdee
https://doi.org/10.1016/j.ecolmodel.2014.03.017