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-4.5)cjbart_0.3.2.zip(r-4.4)cjbart_0.3.2.zip(r-4.3)
cjbart_0.3.2.tgz(r-4.5-any)cjbart_0.3.2.tgz(r-4.4-any)cjbart_0.3.2.tgz(r-4.3-any)
cjbart_0.3.2.tar.gz(r-4.5-noble)cjbart_0.3.2.tar.gz(r-4.4-noble)
cjbart_0.3.2.tgz(r-4.4-emscripten)cjbart_0.3.2.tgz(r-4.3-emscripten)
cjbart.pdf |cjbart.html✨
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:

4.65 score 9 stars 4 scripts 386 downloads 7 exports 79 dependencies

Last updated 2 years agofrom:b13ecf8399. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 27 2025
R-4.5-winOKFeb 27 2025
R-4.5-macOKFeb 27 2025
R-4.5-linuxOKFeb 27 2025
R-4.4-winOKFeb 27 2025
R-4.4-macOKFeb 27 2025
R-4.3-winOKFeb 27 2025
R-4.3-macOKFeb 27 2025

Exports:AMCEcjbarthet_vimpIMCEpIMCErf_vimpRMCE

Dependencies:BARTbase64encbitbit64bslibcachemclicliprcolorspacecpp11crayondata.treeDiagrammeRdigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhmshtmltoolshtmlwidgetsigraphisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigprettyunitsprogresspurrrR6randomForestSRCrappdirsrbibutilsRColorBrewerRcppRdpackreadrrlangrmarkdownrstudioapisassscalesstringistringrsurvivaltibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml

Introduction to heterogeneous effects analysis of conjoint experiments using cjbart

Rendered fromcjbart-demo.Rmdusingknitr::rmarkdownon Feb 27 2025.

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