Package: RoBTT
Title: Robust Bayesian T-Test
Version: 1.1.0
Maintainer: František Bartoš <f.bartos96@gmail.com>
Authors@R: c( 
    person("František", "Bartoš",     role = c("aut", "cre"),
    email   = "f.bartos96@gmail.com", comment = c(ORCID = "0000-0002-0018-5573")),
    person("Maximilian", "Maier",     role = "aut",
    email   = "maximilianmaier0401@gmail.com", comment = c(ORCID = "0000-0002-9873-6096"))
    )
Description: 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.
URL: https://fbartos.github.io/RoBTT/
BugReports: https://github.com/FBartos/RoBTT/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
SystemRequirements: GNU make
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
NeedsCompilation: yes
ByteCompile: true
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)
Depends: 
    R (>= 4.0.0),
    Rcpp (>= 0.12.19)
Imports:
    rstan(>= 2.21.2),
    rstantools(>= 1.5.0),
    RcppParallel (>= 5.0.1),
    BayesTools (>= 0.2.14),
    bridgesampling,
    methods,
    ggplot2,
    Rdpack
Suggests:
    parallel,
    testthat,
    vdiffr,
    knitr,
    rmarkdown,
    covr
RdMacros: Rdpack
VignetteBuilder: knitr
