BayesChange: an R package for Bayesian Change Point Analysis

TL;DR

BayesChange is an R package that efficiently detects and clusters change points in data using Bayesian methods, with a user-friendly interface and novel algorithms not available in other packages.

Contribution

It introduces a new Bayesian change point detection package in R with C++ backend, offering methods and algorithms not previously accessible in existing tools.

Findings

Efficient Bayesian change point detection and clustering

Implementation in R with C++ for speed

Validated with synthetic data examples

Abstract

We introduce BayesChange, a computationally efficient R package, built on C++, for Bayesian change point detection and clustering of observations sharing common change points. While many R packages exist for change point analysis, BayesChange offers methods not currently available elsewhere. The core functions are implemented in C++ to ensures computational efficiency, while an R user interface simplifies the package usage. The BayesChange package includes two R wrappers that integrate the C++ backend functions, along with S3 methods for summarizing the results. We present the theory beyond each method, the algorithms for posterior simulation and we illustrate the package's usage through synthetic examples.