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scalablebayesm: Distributed Markov Chain Monte Carlo for Bayesian Inference inMarketing

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.

Version:0.2
Imports:Rcpp (≥ 1.0.9), parallel,bayesm
LinkingTo:Rcpp,RcppArmadillo,bayesm
Published:2025-02-25
DOI:10.32614/CRAN.package.scalablebayesm
Author:Federico Bumbaca [aut, cre], Jackson Novak [aut]
Maintainer:Federico Bumbaca <federico.bumbaca at colorado.edu>
License:GPL-2 |GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:yes
CRAN checks:scalablebayesm results

Documentation:

Reference manual:scalablebayesm.html ,scalablebayesm.pdf

Downloads:

Package source: scalablebayesm_0.2.tar.gz
Windows binaries: r-devel:scalablebayesm_0.2.zip, r-release:scalablebayesm_0.2.zip, r-oldrel:scalablebayesm_0.2.zip
macOS binaries: r-release (arm64):scalablebayesm_0.2.tgz, r-oldrel (arm64):scalablebayesm_0.2.tgz, r-release (x86_64):scalablebayesm_0.2.tgz, r-oldrel (x86_64):scalablebayesm_0.2.tgz

Linking:

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