mcp: An R Package for Regression With Multiple Change Points
Jonas Kristoffer Lindeløv
Abstract
The R package mcp does flexible and informed Bayesian regression with change points. mcp can infer the location of changes between regression models on means, variances, autocorrelation structure, and any combination of these. Prior and posterior samples and summaries are returned for all parameters and a rich set of plotting options is available. Bayes Factors can be computed via Savage-Dickey density ratio and posterior contrasts. Cross-validation can be used for more general model comparison. mcp ships with sensible defaults, including priors, but the user can override them to get finer control of the models and outputs. The strengths and limitations of mcp are discussed in relation to existing change point packages in R.