This R package evaluates through the Bayes Factor whether two sets of samples come from the same Multivariate Gaussian distribution or not.
It currently implements a fast Gibbs sampler for the Multivariate Normal - Inverse Wishart model.
The package is not on CRAN yet.
It must be installed using devtools or remotes from this repository:
# install.packages('remotes')
remotes::install_github('lgaborini/bayessource')
Documentation is available on GitHub pages, or in the docs/index.html file of the repository.
Also see the vignettes:
make_priors_and_init(): obtain hyperpriors and initialization from a background datasetmarginalLikelihood(): fast computation of the marginal likelihoodsamesource_C(): fast computation of the Bayes Factor (same source vs. different sources)mcmc_postproc(): collect and tidy posterior samples from this package
The documentation uses some roxygen2 Rd templates to enter parametrization/model details.
These are stored in the directory man-roxygen.
When updating Rd templates, one must pay attenton that:
- LaTeX is supported only through the Rd
\eqn{latex}{ascii}and\deqn{latex}{ascii}tags. - it is best to write plain Rd or roxygen2 tags rather than Markdown tags
- sections must start with the
\@section title:and end up after the Details. Do not forget the:at the end.
Bozza, Taroni, Marquis, Schmittbuhl, “Probabilistic Evaluation of Handwriting Evidence: Likelihood Ratio for Authorship.” Journal of the Royal Statistical Society: Series C (Applied Statistics) 57, no. 3 (June 1, 2008): 329–41. https://doi.org/10.1111/j.1467-9876.2007.00616.x.