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: 2026-10-14 10:06:44 UTC; root
Author: Federico Bumbaca [aut, cre], Jackson Novak [aut]
Repository: https://cran.r-universe.dev
Date/Publication: 2025-02-25 12:30:02 UTC
RemoteUrl: https://github.com/cran/scalablebayesm
RemoteRef: HEAD
RemoteSha: 9b4927b7d907652e352744ecab6295b46b56ff16