RoBTT: Robust Bayesian T-Test

An implementation of Bayesian model-averaged t-test that allows users to draw inference about the presence vs absence of the effect, heterogeneity of variances, and outliers. The 'RoBTT' packages estimates model ensembles of models created as a combination of the competing hypotheses and uses Bayesian model-averaging to combine the models using posterior model probabilities. Users can obtain the model-averaged posterior distributions and inclusion Bayes factors which account for the uncertainty in the data generating process (Maier et al., 2022, <doi:10.31234/>). Users can define a wide range of informative priors for all parameters of interest. The package provides convenient functions for summary, visualizations, and fit diagnostics.

Version: 1.3.0
Depends: R (≥ 4.0.0), Rcpp (≥ 0.12.19)
Imports: rstan (≥ 2.26.0), rstantools (≥ 1.5.0), RcppParallel (≥ 5.0.1), BayesTools (≥ 0.2.15), bridgesampling, methods, ggplot2, Rdpack
LinkingTo: StanHeaders (≥ 2.26.0), rstan (≥ 2.26.0), BH (≥ 1.69.0), Rcpp (≥ 0.12.15), RcppEigen (≥, RcppParallel (≥ 5.0.1)
Suggests: parallel, testthat, vdiffr, knitr, rmarkdown, covr
Published: 2024-04-04
DOI: 10.32614/CRAN.package.RoBTT
Author: František Bartoš ORCID iD [aut, cre], Maximilian Maier ORCID iD [aut], Henrik R Godmann ORCID iD [aut]
Maintainer: František Bartoš <f.bartos96 at>
License: GPL-3
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: RoBTT citation info
Materials: README NEWS
CRAN checks: RoBTT results


Reference manual: RoBTT.pdf
Vignettes: Introduction to RoBTT
Truncated Bayesian Model-Averaged T-Test


Package source: RoBTT_1.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): RoBTT_1.3.0.tgz, r-oldrel (arm64): RoBTT_1.3.0.tgz, r-release (x86_64): RoBTT_1.3.0.tgz, r-oldrel (x86_64): RoBTT_1.3.0.tgz
Old sources: RoBTT archive


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