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/osf.io/d5zwc>).
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: |
1.0.0 |
| Depends: |
R (≥ 4.0.0), Rcpp (≥ 0.12.19) |
| Imports: |
rstan (≥ 2.21.2), rstantools (≥ 1.5.0), RcppParallel (≥
5.0.1), BayesTools (≥ 0.2.12), bridgesampling, methods, Rdpack |
| LinkingTo: |
StanHeaders (≥ 2.18.1), rstan (≥ 2.21.2), BH (≥ 1.69.0), Rcpp (≥ 0.12.15), RcppEigen (≥ 0.3.3.4.0), RcppParallel (≥
5.0.1) |
| Suggests: |
parallel, testthat, vdiffr, knitr, rmarkdown, covr |
| Published: |
2022-09-20 |
| Author: |
František Bartoš 
[aut, cre],
Maximilian Maier
[aut] |
| Maintainer: |
František Bartoš <f.bartos96 at gmail.com> |
| BugReports: |
https://github.com/FBartos/RoBTT/issues |
| License: |
GPL-3 |
| URL: |
https://fbartos.github.io/RoBTT/ |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Citation: |
RoBTT citation info |
| Materials: |
README |
| CRAN checks: |
RoBTT results |
Documentation:
Downloads:
Linking:
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