Bayesian Spatial and Space-Time Linear Mixed Models R package stLMM version 0.0.3 CRAN Task View: MixedModels (https://CRAN.R-project.org/view=MixedModels) Fits Bayesian linear mixed models for spatial and space-time data with fixed effects, independent and identically distributed (iid) grouped random effects, and structured latent processes. The formula interface supports first-order autoregressive (AR(1)) effects, dense Gaussian processes, nearest-neighbor Gaussian processes, proper and Leroux conditional autoregressive (CAR) effects, ordered directed acyclic graph autoregressive (DAGAR) effects, separable CAR-time and DAGAR-time effects, and spatially varying coefficients. The sampler uses sparse precision matrix calculations when available and includes post-fitting tools for latent process recovery, fitted values, prediction, pointwise log likelihoods, and posterior sample extraction. Method details include Datta et al. (2016) <doi:10.1080/01621459.2015.1044091>, Finley et al. (2019) <doi:10.1080/10618600.2018.1537924>, Datta et al. (2019) <doi:10.1214/19-BA1177>, and May and Finley (2025) <doi:10.1016/j.spasta.2025.100917>. Software Depends: R (>= 4.4.0) Imports: BayesLogit (>= 2.4), coda, Matrix (>= 1.7-0), stats LinkingTo: BayesLogit (>= 2.4), Matrix (>= 1.7-0) Suggests: ggplot2, knitr, loo, quarto, sf, testthat (>= 3.0.0) Andrew O. Finley <finleya@msu.edu> Comprehensive R Archive Network (CRAN) Andrew O. Finley [aut, cre], Sudipto Banerjee [ctb], Abhirup Datta [ctb], Paul B. May [ctb] GPL (>= 3) 2026-07-29 application/tgz https://CRAN.R-project.org/package=stLMM doi:10.32614/CRAN.package.stLMM