Multivariate Changepoint Problem

Likelihood Asymptotics for Changepoint Problem

Changepoint problems are often encountered when series undergo abrupt changes or discontinuities. Detecting changepoints can signal useful actions towards sustainable developments. However the presence of changepoints have often been known to lead to failure of some regular assumptions. In theory much has not been done on which assumptions fail and to what extent will it affect the score functi...

Performance analysis for a changepoint problem

Nonlinear stochastic diierential equations are used to model a version of the changepoint problem. State estimates of the minimum-mean-square-error type are used in likelihood-ratio tests to detect the time of change. We then evaluate how well the system performs by deriving theoretical expressions for the false alarm probability and a special case of the miss error probability. The approach us...

changepoint: An R Package for Changepoint Analysis

One of the key challenges in changepoint analysis is the ability to detect multiple changes within a given time series or sequence. The changepoint package has been developed to provide users with a choice of multiple changepoint search methods to use in conjunction with a given changepoint method and in particular provides an implementation of the recently proposed PELT algorithm. This article...

Isotonic regression: Another look at the changepoint problem

where the m k are the means and Z k is a stationary process with mean 0 and finite covariances c(k)=cov (Z i , Z i+k )=E(Z0Zk). For this scenario, there has been both classical work on testing for the existence of a trend and more recent work on tests for an abrupt change. The present work falls between these two approaches in developing a test for a change, or trend, that is monotonic but othe...

Analysis of Changepoint Models