Bayesian Analysis of Change Point Problems

Provides an implementation of the Barry and Hartigan (1993) product partition model for the normal errors change point problem using Markov Chain Monte Carlo. It also extends the methodology to regression models on a connected graph (Wang and Emerson, 2015); this allows estimation of change point models with multivariate responses. Parallel MCMC, previously available in bcp v.3.0.0, is currently not implemented.


bcp is an R package that provides an implementation of the Barry and Hartigan (1993) product partition model for the normal errors change point problem using Markov Chain Monte Carlo. It also extends the methodology to regression models on a connected graph (Wang and Emerson, 2015); this allows estimation of change point models with multivariate responses. Parallel MCMC, previously available in bcp v.3.0.0, is currently not implemented.

To install:

  • the latest released version: install.packages("bcp")
  • the latest development version: install_github("swang87/bcp")

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Reference manual

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install.packages("bcp")

4.0.0 by John W. Emerson, 2 years ago


Browse source code at https://github.com/cran/bcp


Authors: Xiaofei Wang, Chandra Erdman, and John W. Emerson


Documentation:   PDF Manual  


Task views: Bayesian Inference, High-Performance and Parallel Computing with R


GPL (>= 2) license


Imports Rcpp

Depends on graphics, methods, grid

Suggests DNAcopy, coda, strucchange, vegan, ggplot2, igraph

Linking to Rcpp, RcppArmadillo


Imported by phenopix.

Suggested by fPortfolio.


See at CRAN