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glmmfields (version 0.1.7)

Generalized Linear Mixed Models with Robust Random Fields for Spatiotemporal Modeling

Description

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) .

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Install

install.packages('glmmfields')

Monthly Downloads

770

Version

0.1.7

License

GPL (>= 3)

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Maintainer

Sean Anderson

Last Published

March 10th, 2023

Functions in glmmfields (0.1.7)

glmmfields

Fit a spatiotemporal random fields GLMM
lognormal

Lognormal family
format_data

Format data for fitting a glmmfields model
plot.glmmfields

Plot predictions from an glmmfields model
glmmfields-package

The 'glmmfields' package.
predict

Predict from a glmmfields model
loo.glmmfields

Return LOO information criteria
student_t

Student-t and half-t priors
sim_glmmfields

Simulate a random field with a MVT distribution
nbinom2

Negative binomial family
stan_pars

Return a vector of parameters
tidy

Tidy model output