bcp v4.0.3

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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.

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bcp

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")

Functions in bcp

Name Description
residuals.bcp Extract model residuals
legacyplot Plotting univariate Bayesian change point results
summary.bcp Summarizing Bayesian change point analysis results
makeAdjGrid Creating the adjacency structure for grid graphs
plot.bcp Plotting Bayesian change point results
fitted.bcp Extract model fitted values
RealInt US Ex-post Real Interest Rate data, 1961(1):1986(3)
bcp-package Bayesian Analysis of Change Point Problems
interval.prob Estimate the probability of a change point in a specified interval
bcp Performs a Bayesian analysis of change point problems
coriell Array CGH data set of Coriell cell lines
lombard Milling machine indentation data
NewHavenHousing New Haven housing data
QuebecRivers Quebec river streamflow data
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Details

Type Package
Date 2018-08-13
License GPL (>= 2)
LinkingTo Rcpp, RcppArmadillo
NeedsCompilation yes
Repository CRAN
Encoding UTF-8
RoxygenNote 6.1.0
Packaged 2018-08-13 19:10:46 UTC; eastie
Date/Publication 2018-08-13 19:40:03 UTC

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