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scalablebayesm  

Distributed Markov Chain Monte Carlo for Bayesian Inference in Marketing
View on CRAN: Click here


Download and install scalablebayesm package within the R console
Install from CRAN:
install.packages("scalablebayesm")

Install from Github:
library("remotes")
install_github("cran/scalablebayesm")

Install by package version:
library("remotes")
install_version("scalablebayesm", "0.2")



Attach the package and use:
library("scalablebayesm")
Maintained by
Federico Bumbaca
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-02-25
Latest Update: 2025-02-25
Description:
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.
How to cite:
Federico Bumbaca (2025). scalablebayesm: Distributed Markov Chain Monte Carlo for Bayesian Inference in Marketing. R package version 0.2, https://cran.r-project.org/web/packages/scalablebayesm. Accessed 25 Oct. 2026.
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