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scalablebayesm: Distributed Markov Chain Monte Carlo for Bayesian Inference in Marketing
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.
Getting started
Browse package contents
Package details |
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| Author | Federico Bumbaca [aut, cre], Jackson Novak [aut] |
| Maintainer | Federico Bumbaca <federico.bumbaca@colorado.edu> |
| License | GPL (>= 2) |
| Version | 0.2 |
| Package repository | View on CRAN |
| Installation |
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