A BAYESIAN SEMIPARAMETRIC JOLLY-SEBER MODEL WITH INDIVIDUAL HETEROGENEITY: AN APPLICATION TO MIGRATORY MALLARDS AT STOPOVER

• 成果类型: Article
• 署名作者: Wu, Guohui; Holan, Scott H.; Avril, Alexis; Waldenstrom, Jonas
• 署名单位: SAS Institute Inc; University of Missouri System; University of Missouri Columbia; Linnaeus University
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/20-AOAS1421
• 发表日期: 2021
• 页码: 813-830
• 关键词: capture-recapture; population-size; survival; time; regression

摘要

We propose a Bayesian hierarchical Jolly-Seber model that can accommodate a semiparametric functional relationship between external covariates and capture probabilities, individual heterogeneity in departure due to an internal time-varying covariate and the dependence of arrival time on external covariates. Modelwise, we consider a stochastic process to characterize the evolution of the partially observable internal covariate that is linked to departure probabilities. Computationally, we develop a well-tailored Markov chain Monte Carlo algorithm that is free of tuning through data augmentation. Inferentially, our model allows us to make inference about stopover duration and population sizes, the impacts of various covariates on departure and arrival time and to identify flexible yet data-driven functional relationships between external covariates and capture probabilities. We demonstrate the effectiveness of our model through a motivating dataset collected for studying the migration of mallards (Arias platyrhynchos) in Sweden.