Package: scalablebayesm 0.2

Federico Bumbaca
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.
Authors:
scalablebayesm_0.2.tar.gz
scalablebayesm_0.2.tar.gz(r-4.7-arm64)scalablebayesm_0.2.tar.gz(r-4.7-x86_64)scalablebayesm_0.2.tar.gz(r-4.6-arm64)scalablebayesm_0.2.tar.gz(r-4.6-x86_64)
scalablebayesm_0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
scalablebayesm/json (API)
| # Install 'scalablebayesm' in R: |
| install.packages('scalablebayesm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:9b4927b7d9. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 191 | ||
| linux-devel-x86_64 | OK | 233 | ||
| source / vignettes | OK | 245 | ||
| linux-release-arm64 | OK | 198 | ||
| linux-release-x86_64 | OK | 220 | ||
| wasm-release | OK | 144 |
Exports:combine_drawsdrawMixturedrawPosteriorParallelhellopartition_datarheteroLinearIndepMetroprheteroMnlIndepMetroprhierLinearDPParallelrhierLinearMixtureParallelrhierMnlDPParallelrhierMnlRwMixtureParallels_maxsample_data
Dependencies:bayesmRcppRcppArmadillo