glmmfields: Generalized Linear Mixed Models with Robust Random Fields for Spatiotemporal Modeling (original) (raw)

Implements Bayesian spatial and spatiotemporal models that optionally allow for extreme spatial deviations through time. 'glmmfields' uses a predictive process approach with random fields implemented through a multivariate-t distribution instead of the usual multivariate normal. Sampling is conducted with 'Stan'. References: Anderson and Ward (2019) <doi:10.1002/ecy.2403>.

Version:

0.1.8

Depends:

methods, R (≥ 3.4.0), Rcpp (≥ 0.12.18)

Imports:

assertthat, broom, broom.mixed, cluster, dplyr (≥ 0.8.0), forcats, ggplot2 (≥ 2.2.0), loo (≥ 2.0.0), mvtnorm, nlme, RcppParallel (≥ 5.0.1), reshape2, rstan (≥ 2.26.0), rstantools (≥ 2.1.1), tibble