Bayesian Spatial Panel Data Models with Convex Combinations of Weight Matrices R package spmixW version 0.2.2 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). Software Depends: R (>= 4.1.0) Imports: Matrix, MASS, coda Suggests: testthat (>= 3.0.0), knitr, rmarkdown, spdep, sf, ggplot2, broom Mustapha Wasseja Mohammed <muswaseja@gmail.com> Comprehensive R Archive Network (CRAN) Mustapha Wasseja Mohammed [aut, cre] GPL (>= 3) 2026-04-16 application/tgz https://CRAN.R-project.org/package=spmixW doi:10.32614/CRAN.package.spmixW