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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 |
| Reference manual: | scalablebayesm.pdf |
| 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-devel (arm64): scalablebayesm_0.2.tgz, r-release (arm64): scalablebayesm_0.2.tgz, r-oldrel (arm64): scalablebayesm_0.2.tgz, r-devel (x86_64): scalablebayesm_0.2.tgz, r-release (x86_64): scalablebayesm_0.2.tgz, r-oldrel (x86_64): scalablebayesm_0.2.tgz |
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