Bayesian Analysis

Intrinsic Bayesian Analysis for Occupancy Models

Daniel Taylor-Rodríguez, Andrew J. Womack, Claudio Fuentes, and Nikolay Bliznyuk

Full-text: Open access

Abstract

Occupancy models are typically used to determine the probability of a species being present at a given site while accounting for imperfect detection. The survey data underlying these models often include information on several predictors that could potentially characterize habitat suitability and species detectability. Because these variables might not all be relevant, model selection techniques are necessary in this context. In practice, model selection is performed using the Akaike Information Criterion (AIC), as few other alternatives are available. This paper builds an objective Bayesian variable selection framework for occupancy models through the intrinsic prior methodology. The procedure incorporates priors on the model space that account for test multiplicity and respect the polynomial hierarchy of the predictors when higher-order terms are considered. The methodology is implemented using a stochastic search algorithm that is able to thoroughly explore large spaces of occupancy models. The proposed strategy is entirely automatic and provides control of false positives without sacrificing the discovery of truly meaningful covariates. The performance of the method is evaluated and compared to AIC through a simulation study. The method is illustrated on two datasets previously studied in the literature.

Article information

Source
Bayesian Anal., Volume 12, Number 3 (2017), 855-877.

Dates
First available in Project Euclid: 9 September 2016

Permanent link to this document
https://projecteuclid.org/euclid.ba/1473431536

Digital Object Identifier
doi:10.1214/16-BA1014

Mathematical Reviews number (MathSciNet)
MR3655879

Zentralblatt MATH identifier
1384.62107

Keywords
imperfect detection intrinsic priors model priors strong heredity Bayesian variable selection AIC

Rights
Creative Commons Attribution 4.0 International License.

Citation

Taylor-Rodríguez, Daniel; Womack, Andrew J.; Fuentes, Claudio; Bliznyuk, Nikolay. Intrinsic Bayesian Analysis for Occupancy Models. Bayesian Anal. 12 (2017), no. 3, 855--877. doi:10.1214/16-BA1014. https://projecteuclid.org/euclid.ba/1473431536


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