Modeling Spatial Covariance Using the Limiting Distribution of Spatio-Temporal Random Walks

• 成果类型: Article
• 署名作者: Hanks, Ephraim M.
• 署名单位: Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2016.1224714
• 发表日期: 2017
• 页码: 497-507
• 关键词: population-structure; bayesian-inference; circuit-theory; FRAMEWORK; MOVEMENT; genetics; ecology; scale

摘要

We present an approach for modeling areal spatial covariance in observed genetic allele data by considering the stationary (limiting) distribution of a spatio-temporal Markov random walk model for gene flow. This stationary distribution corresponds to an intrinsic simultaneous autoregressive (SAR) model for spatial correlation, and provides a principled approach to specifying areal spatial models when a spatio-temporal generating process can be assumed. We apply the approach to a study of spatial genetic variation of trout in a stream network in Connecticut, USA.