Distributed Markov Chain Monte Carlo for Bayesian Inference in Marketing R package scalablebayesm version 0.2 Estimates unit-level and population-level parameters from a hierarchical model in marketing applications. The package includes: Hierarchical Linear Models with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates. For more details, see Bumbaca, F. (Rico), Misra, S., & Rossi, P. E. (2020) <doi:10.1177/0022243720952410> "Scalable Target Marketing: Distributed Markov Chain Monte Carlo for Bayesian Hierarchical Models". Journal of Marketing Research, 57(6), 999-1018. Software Imports: Rcpp (>= 1.0.9), parallel, bayesm LinkingTo: Rcpp, RcppArmadillo, bayesm Federico Bumbaca <federico.bumbaca@colorado.edu> Comprehensive R Archive Network (CRAN) Federico Bumbaca [aut, cre], Jackson Novak [aut] GPL (>= 2) 2025-02-25 application/tgz https://CRAN.R-project.org/package=scalablebayesm doi:10.32614/CRAN.package.scalablebayesm