Package: cjbart 0.3.2

cjbart: Heterogeneous Effects Analysis of Conjoint Experiments

A tool for analyzing conjoint experiments using Bayesian Additive Regression Trees ('BART'), a machine learning method developed by Chipman, George and McCulloch (2010) <doi:10.1214/09-AOAS285>. This tool focuses specifically on estimating, identifying, and visualizing the heterogeneity within marginal component effects, at the observation- and individual-level. It uses a variable importance measure ('VIMP') with delete-d jackknife variance estimation, following Ishwaran and Lu (2019) <doi:10.1002/sim.7803>, to obtain bias-corrected estimates of which variables drive heterogeneity in the predicted individual-level effects.

Authors:Thomas Robinson [aut, cre, cph], Raymond Duch [aut, cph]

cjbart_0.3.2.tar.gz
cjbart_0.3.2.zip(r-4.7)cjbart_0.3.2.zip(r-4.6)cjbart_0.3.2.zip(r-4.5)
cjbart_0.3.2.tgz(r-4.6-any)cjbart_0.3.2.tgz(r-4.5-any)
cjbart_0.3.2.tar.gz(r-4.7-any)cjbart_0.3.2.tar.gz(r-4.6-any)
cjbart_0.3.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
cjbart/json (API)
NEWS

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

Bug tracker:https://github.com/tsrobinson/cjbart/issues

On CRAN:

Conda:

4.70 score 10 stars 4 scripts 220 downloads 7 exports 75 dependencies

Last updated from:b13ecf8399. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK167
source / vignettesOK227
linux-release-x86_64OK156
macos-release-arm64OK142
macos-oldrel-arm64OK174
windows-develOK107
windows-releaseOK113
windows-oldrelOK137
wasm-releaseOK132

Exports:AMCEcjbarthet_vimpIMCEpIMCErf_vimpRMCE

Dependencies:BARTbase64encbitbit64bslibcachemclicliprcpp11crayondata.treeDiagrammeRdigestdplyrevaluatefarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhmshtmltoolshtmlwidgetsigraphisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmemoisemimenlmepillarpkgconfigprettyunitsprogresspurrrR6randomForestSRCrappdirsrbibutilsRColorBrewerRcppRdpackreadrrlangrmarkdownrstudioapiS7sassscalesstringistringrsurvivaltibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml

Introduction to heterogeneous effects analysis of conjoint experiments using cjbart

Rendered fromcjbart-demo.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2023-09-06
Started: 2020-12-01