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stLMM  

Bayesian Spatial and Space-Time Linear Mixed Models
View on CRAN: Click here


Download and install stLMM package within the R console
Install from CRAN:
install.packages("stLMM")

Install from Github:
library("remotes")
install_github("cran/stLMM")

Install by package version:
library("remotes")
install_version("stLMM", "0.0.3")



Attach the package and use:
library("stLMM")
Maintained by
Andrew O. Finley
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-30
Latest Update: 2026-07-29
Description:
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>.
How to cite:
Andrew O. Finley (2026). stLMM: Bayesian Spatial and Space-Time Linear Mixed Models. R package version 0.0.3, https://cran.r-project.org/web/packages/stLMM. Accessed 20 Sep. 2026.
Previous versions and publish date:
(2026-07-30 00:10), 0.0.2 (2026-07-28 18:30)
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View stLMM citation profile
Other R packages that stLMM depends, imports, suggests or enhances
Complete documentation for stLMM
Functions, R codes and Examples using the stLMM R package
Full stLMM package functions and examples
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