/solocp

R package complementing an upcoming draft

Primary LanguageR

solocp

solocp includes a fast Bayesian change point detection methodology based on spike and slab priors.

Installation

  1. Install the package devtools

  2. Load devtools using library(devtools).

  3. Install solocp using

    1. install_github("lorenzocapp/solocp"), or

    2. install_github("lorenzocapp/solocp", build_vignettes = TRUE) if you want some illustrative vignettes (note: using build_vignettes = TRUE will make the install take longer).

Vignettes

  1. solocp_simulated_data: A short tutorial to describe the basics functioning of the package.

References

  1. Cappello, L., Madrid Padilla, O. H., Palacios, J. A. (2022), Bayesian change point detection with spike and slab priors. arXiv

Numerical Experiments in the Manuscript

The draft includes several numerical experiments. These can be found at this link. While they are based on the same methodology, they rely on a less user-friendly implementation of the functions included in this package.