glmmfields (0.1.3)

0 users

Generalized Linear Mixed Models with Robust Random Fields for Spatiotemporal Modeling.

https://github.com/seananderson/glmmfields
http://cran.r-project.org/web/packages/glmmfields

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) .

Maintainer: Sean C. Anderson
Author(s): Sean C. Anderson [aut, cre], Eric J. Ward [aut], Trustees of Columbia University [cph]

License: GPL (>= 3)

Uses: assertthat, broom, cluster, dplyr, forcats, ggplot2, loo, mvtnorm, nlme, Rcpp, reshape2, rstan, rstantools, coda, testthat, knitr, rmarkdown, viridis, bayesplot

Released about 1 month ago.


3 previous versions

Ratings

Overall:

  (0 votes)

Documentation:

  (0 votes)

Log in to vote.

Reviews

No one has written a review of glmmfields yet. Want to be the first? Write one now.


Related packages:(20 best matches, based on common tags.)


Search for glmmfields on google, google scholar, r-help, r-devel.

Visit glmmfields on R Graphical Manual.