%0 Journal Article %1 hanks2017modeling %A Hanks, Ephraim M. %D 2017 %I Taylor & Francis %J Journal of the American Statistical Association %K Matern_covariances coalescing_random_walk diffusion_approximation geographic_methods population_genetics spatial_coalescent %N 518 %P 497-507 %R 10.1080/01621459.2016.1224714 %T Modeling Spatial Covariance Using the Limiting Distribution of Spatio-Temporal Random Walks %U https://doi.org/10.1080/01621459.2016.1224714 %V 112 %X 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.

@article{hanks2017modeling, abstract = {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. }, added-at = {2017-12-14T23:07:06.000+0100}, author = {Hanks, Ephraim M.}, biburl = {https://www.bibsonomy.org/bibtex/2fb00c778bd3b3e74c2788b5b5322c544/peter.ralph}, description = {Discusses asymmetry, with application to trout in a stream network. Has a mixed model where the driving Gaussian noise has the covariance function of the stationary distribution of a discrete-space-time random field. The random field is a discrete model of abundance with sources, sinks, and migration - reaction-diffusion with diffusion from a MC and reaction equal to births minus deaths; and modeling the reaction term as spatial white noise. No reasons are given why the covariance function for space-time abundance should equal the covariance function underlying allelic identity. }, doi = {10.1080/01621459.2016.1224714}, eprint = {https://doi.org/10.1080/01621459.2016.1224714}, interhash = {f88c293638de7849c307be1f5d046eb7}, intrahash = {fb00c778bd3b3e74c2788b5b5322c544}, journal = {Journal of the American Statistical Association}, keywords = {Matern_covariances coalescing_random_walk diffusion_approximation geographic_methods population_genetics spatial_coalescent}, number = 518, pages = {497-507}, publisher = {Taylor \& Francis}, timestamp = {2018-08-20T07:23:12.000+0200}, title = {Modeling Spatial Covariance Using the Limiting Distribution of Spatio-Temporal Random Walks}, url = {https://doi.org/10.1080/01621459.2016.1224714}, volume = 112, year = 2017 }