Package index

All functions

as_mcmc()

Convert stLMM samples to coda objects

as_samples()

Collect stLMM posterior samples in a data frame

car_graph() plot(<stLMM_car_graph>) plot(<stLMM_graph>)

Build a CAR adjacency graph

fitted(<stLMM>)

Posterior fitted values for an stLMM fit

get_cor_models()

List supported covariance models

log_lik() waic()

Pointwise log likelihood and WAIC

predict(<stLMM>) predict(<stLMM_chains>) predict(<stLMM_recovery>) predict(<stLMM_recovery_chains>)

Posterior prediction from recovered stLMM fits

recover()

Recover latent process draws

resid()

Residual variance formula term

print(<stLMM>) summary(<stLMM>) plot(<stLMM>) print(<stLMM_chains>) summary(<stLMM_chains>) plot(<stLMM_chains>) print(<stLMM_recovery>) summary(<stLMM_recovery>) summary(<stLMM_recovery_chains>) plot(<stLMM_recovery>) plot(<stLMM_recovery_chains>) print(<stLMM_prediction>) summary(<stLMM_prediction>) plot(<stLMM_prediction>) plot(<stLMM_prediction_chains>)

Print, summarize, and plot stLMM objects

flat() normal() ig() uniform() log_normal() gamma_dist() half_normal() half_t() beta_dist() fixed()

Prior constructors for stLMM

stLMM-terms stLMM_terms iid nngp gp ar1 car car_time dagar dagar_time

stLMM formula terms

stLMM()

Fit a Bayesian mixed model with structured latent processes

stunitco

FIA state, unit, and county polygons