Bayesian model selection for spatial capture-recapture models.

ABSTRACT: A vast amount of ecological knowledge generated over the past two decades has hinged upon the ability of model selection methods to discriminate among various ecological hypotheses. The last decade has seen the rise of Bayesian hierarchical models in ecology. Consequently, commonly used tools, such as the AIC, become largely inapplicable and there appears to be no consensus about a particular model selection tool that can be universally applied. We focus on a specific class of competing Bayesian spatial capture-recapture (SCR) models and apply and evaluate some of the recommended Bayesian model selection tools: (1) Bayes Factor-using (a) Gelfand-Dey and (b) harmonic mean methods, (2) Deviance Information Criterion (DIC), (3) Watanabe-Akaike's Information Criterion (WAIC) and (4) pos

SUBMITTER: Dey S 

PROVIDER: S-EPMC6822056 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature