Bayesian Online Changepoint Detection

Implements the Bayesian online changepoint detection method by Adams and MacKay (2007) for univariate or multivariate data. Gaussian and Poisson probability models are implemented. Provides post-processing functions with alternative ways to extract changepoints.


The goal of ocp is to implement Bayesian Online Changepoint Detection, as described: https://arxiv.org/abs/0710.3742

Example

This is a basic example of how to use the function "onlineCPD" on simulated univariate Gaussian data as input.

library(ocp)
truecps<- c(1, 51, 71, 121)
#simulate the data
set.seed(1)
uvg<- c(rnorm(n=diff(truecps)[1], mean=0, sd=2), 
        rnorm(n=diff(truecps)[2], mean=20, sd=4),
        rnorm(n=diff(truecps)[3], mean=10, sd=3))
ocpd_output<- onlineCPD(uvg) 

News

Reference manual

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install.packages("ocp")

0.1.1 by Andrea Pagotto, 2 months ago


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


Authors: Andrea Pagotto


Documentation:   PDF Manual  


GPL-3 license


Imports grid, graphics, grDevices

Suggests testthat, knitr, rmarkdown


See at CRAN