SARAR: Bayesian Estimation of Spatial Autoregressive Models with Flexible Error Distributions

Provides Bayesian estimation and inference for spatial autoregressive models with spatial dependence in both the response variable and the error terms. The models accommodate Gaussian, Student-t, Laplace, skew-normal, and skew-Student-t error distributions. Posterior inference is performed using Markov chain Monte Carlo methods. The package also provides posterior summaries, convergence diagnostics, residual analysis, and model comparison criteria, including the Deviance Information Criterion (DIC) and the Watanabe-Akaike Information Criterion (WAIC). See LeSage and Pace (2009, ISBN:9781420064247), "Introduction to Spatial Econometrics".

Version:	0.1.0
Depends:	R (≥ 3.5)
Imports:	Formula, coda, statmod, spdep
Published:	2026-11-14
DOI:	10.32614/CRAN.package.SARAR (may not be active yet)
Author:	Luis Hernando Vanegas [aut, cre], Luz Marina Rondón [aut]
Maintainer:	Luis Hernando Vanegas <lhvanegasp at unal.edu.co>
BugReports:	https://github.com/lhvanegasp/SARAR/issues
License:	GPL (≥ 3)
NeedsCompilation:	no
CRAN checks:	SARAR results

Documentation:

Reference manual:

SARAR.html , SARAR.pdf

Downloads:

Package source:	SARAR_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): SARAR_0.1.0.tgz, r-oldrel (arm64): SARAR_0.1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): SARAR_0.1.0.tgz

Linking:

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