hdpGLM: Hierarchical Dirichlet Process Generalized Linear Models

Implementation of MCMC algorithms to estimate the Hierarchical Dirichlet Process Generalized Linear Model (hdpGLM) presented in the paper Ferrari (2020) Modeling Context-Dependent Latent Heterogeneity, Political Analysis <doi:10.1017/pan.2019.13>.

Version: 1.0.0
Depends: R (≥ 3.3.3)
Imports: coda, dplyr, Hmisc, isotone, questionr, LaplacesDemon, magrittr, MASS, MCMCpack, mvtnorm, Rcpp, purrr, rprojroot, tidyverse, tibble, data.table, ggjoy, ggplot2, stringr, tidyr, ggridges, ggpubr, formula.tools
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
Published: 2020-11-09
Author: Diogo Ferrari [aut, cre]
Maintainer: Diogo Ferrari <diogoferrari at gmail.com>
BugReports: https://github.com/DiogoFerrari/hdpGLM/issues
License: MIT + file LICENSE
URL: https://github.com/DiogoFerrari/hdpGLM
NeedsCompilation: yes
Citation: hdpGLM citation info
Materials: README
CRAN checks: hdpGLM results


Reference manual: hdpGLM.pdf
Vignettes: hdpGLM
Package source: hdpGLM_1.0.0.tar.gz
Windows binaries: r-devel: hdpGLM_1.0.0.zip, r-release: hdpGLM_1.0.0.zip, r-oldrel: hdpGLM_1.0.0.zip
macOS binaries: r-release: hdpGLM_1.0.0.tgz, r-oldrel: hdpGLM_1.0.0.tgz


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