Package: hdpGLM 1.0.4

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> and <doi:10.18637/jss.v107.i10>.

Authors:Diogo Ferrari [aut, cre]

hdpGLM_1.0.4.tar.gz
hdpGLM_1.0.4.zip(r-4.7)hdpGLM_1.0.4.zip(r-4.6)hdpGLM_1.0.4.zip(r-4.5)
hdpGLM_1.0.4.tgz(r-4.6-x86_64)hdpGLM_1.0.4.tgz(r-4.6-arm64)hdpGLM_1.0.4.tgz(r-4.5-x86_64)hdpGLM_1.0.4.tgz(r-4.5-arm64)
hdpGLM_1.0.4.tar.gz(r-4.7-arm64)hdpGLM_1.0.4.tar.gz(r-4.6-arm64)hdpGLM_1.0.4.tar.gz(r-4.7-x86_64)hdpGLM_1.0.4.tar.gz(r-4.6-x86_64)
hdpGLM_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
hdpGLM/json (API)
NEWS

# Install 'hdpGLM' in R:
install.packages('hdpGLM', repos = c('https://diogoferrari.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/diogoferrari/hdpglm/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • welfare - Fake data set with 2000 observations
  • welfare2 - Fake data set with 2000 observations

On CRAN:

Conda:

dirichlet-process-mixtureshierarchical-clusteringnonparametricnonparametricbayesnpbsemi-parametricopenblascpp

4.78 score 12 stars 5 scripts 174 downloads 14 exports 184 dependencies

Last updated from:1fad803c94. Checks:9 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64WARNING267
source / vignettesOK395
linux-release-x86_64WARNING253
macos-release-arm64WARNING170
macos-release-x86_64WARNING477
macos-oldrel-arm64WARNING180
macos-oldrel-x86_64WARNING435
windows-develWARNING214
windows-releaseWARNING223
windows-oldrelWARNING188
wasm-releaseOK214

Exports:classifyhdpGLMhdpGLM_classifyhdpGLM_simParametershdpGLM_simulateDatamcmc_info.dpGLMmcmc_info.hdpGLMnclustersplot_betaplot_beta_simplot_hdpglmplot_pexp_betaplot_tausummary_tidy

Dependencies:abindaskpassbackportsbase64encbitbit64blobbootbroombslibcachemcallrcarcarDatacellrangercheckmateclassclassIntclicliprclustercodacolorspacecommonmarkconflictedcorrplotcowplotcpp11crayoncurldata.tableDBIdbplyrDerivdigestdoBydplyrdtplyre1071evaluatefarverfastmapfontawesomeforcatsforecastforeignFormulaformula.toolsfracdifffsgarglegenericsggplot2ggpubrggrepelggridgesggsciggsignifgluegoogledrivegooglesheets4gridExtragtablehavenhighrHmischmshtmlTablehtmltoolshtmlwidgetshttpuvhttridsisobandisotonejquerylibjsonliteKernSmoothknitrlabelinglabelledLaplacesDemonlaterlatticelifecyclelme4lmtestlubridatemagrittrMASSMatrixMatrixModelsmcmcMCMCpackmemoisemgcvmicrobenchmarkmimeminiUIminqamodelrmvtnormnlmenloptrnnetnnlsnumDerivopenssloperator.toolsotelpbkrtestpillarpkgconfigpngpolynomprettyunitsprocessxprogresspromisesproxypspurrrquantregquestionrR.cacheR.methodsS3R.ooR.utilsR6raggrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreadrreadxlreformulasrematchrematch2reprexrlangrmarkdownrpartrprojrootrstatixrstudioapirvestS7sassscalesselectrshinysourcetoolsSparseMstringistringrstylersurvivalsyssystemfontstextshapingtibbletidyrtidyselecttidyversetimechangetimeDatetinytextzdburcautf8uuidvctrsviridisLitevroomwithrxfunxml2xtableyamlzoo

hdpGLM

Rendered fromhdpGLM.Rmdusingknitr::rmarkdownon Jun 01 2026.

Last update: 2022-05-04
Started: 2020-10-26