spmixW: Bayesian Spatial Panel Data Models with Convex Combinations of Weight Matrices

Bayesian Markov chain Monte Carlo (MCMC) estimation of spatial panel data models including Spatial Autoregressive (SAR), Spatial Durbin Model (SDM), Spatial Error Model (SEM), Spatial Durbin Error Model (SDEM), and Spatial Lag of X (SLX) specifications with fixed effects. Supports convex combinations of multiple spatial weight matrices and Bayesian Model Averaging (BMA) over subsets of weight matrices. Implements the convex combination spatial weight matrix methodology of Debarsy and LeSage (2021) <doi:10.1080/07350015.2020.1840993> and the Bayesian spatial panel data models of LeSage and Pace (2009, ISBN:9781420064247).

Version:	0.2.2
Depends:	R (≥ 4.1.0)
Imports:	Matrix, MASS, coda
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown, spdep, sf, ggplot2, broom
Published:	2026-04-16
DOI:	10.32614/CRAN.package.spmixW (may not be active yet)
Author:	Mustapha Wasseja Mohammed [aut, cre]
Maintainer:	Mustapha Wasseja Mohammed <muswaseja at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	no
CRAN checks:	spmixW results

Documentation:

Reference manual:

spmixW.html , spmixW.pdf

Downloads:

Package source:	spmixW_0.2.2.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

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