README.md

In lgaborini/bayessource: Bayesian approach to evaluate whether two datasets come from the same population

bayessource

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.

Installation

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

Documentation is available on GitHub pages, or in the docs/index.html file of the repository.

Also see the vignettes:

• Introduction
• Prior elicitation

Main functions

• make_priors_and_init(): obtain hyperpriors and initialization from a background dataset
• marginalLikelihood(): fast computation of the marginal likelihood
• samesource_C(): fast computation of the Bayes Factor (same source vs. different sources)
• mcmc_postproc(): collect and tidy posterior samples from this package

Extending

Writing Rd documentation

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.

References

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.

lgaborini/bayessource documentation built on Nov. 9, 2021, 2:10 p.m.