Package: scalablebayesm
Type: Package
Title: Distributed Markov Chain Monte Carlo for Bayesian Inference in
        Marketing
Version: 0.2
Date: 2025-01-28
Authors@R: c(
    person(given = "Federico",
           family = "Bumbaca",
           role = c("aut", "cre"),
           email = "federico.bumbaca@colorado.edu"),
    person(given = "Jackson",
           family = "Novak",
           role = "aut"))
Maintainer: Federico Bumbaca <federico.bumbaca@colorado.edu>
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.
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.3.1
Imports: Rcpp (>= 1.0.9), parallel, bayesm
LinkingTo: Rcpp, RcppArmadillo, bayesm
NeedsCompilation: yes
Packaged: 2025-02-23 19:33:42 UTC; jacknovak
Author: Federico Bumbaca [aut, cre],
  Jackson Novak [aut]
Repository: CRAN
Date/Publication: 2025-02-25 12:30:02 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-27 02:50:35 UTC; unix
Archs: scalablebayesm.so.dSYM
