stLMM
0.0.3Bayesian Spatial and Space-Time Linear Mixed Models
Overview
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.
Install
Health
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE r-devel-windows-x86_64
- NOTE2026-07-319 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-07-292 OK · 0 NOTE · 0 WARNING · 5 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 73%
- Return-value docs
- 100%
- References docs
- 14%
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Code & Tests
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2 releases. Pick two to compare their code metrics. R releases are shown for context.
- 0.0.3Latest
- 0.0.22026-07-28
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-07-28
- Total releases
- 2 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.4.0
- Bundled data
- 1.7 MB / 1 file
- Download size
- not tracked yet
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