Article ID Journal Published Year Pages File Type
1146831 Journal of Multivariate Analysis 2006 21 Pages PDF
Abstract

The modified information criterion (MIC) is applied to detect multiple change points in a sequence of independent random variables. We find that the method is consistent in selecting the correct model, and the resulting test statistic has a simple limiting distribution. We show that the estimators for locations of change points achieve the best convergence rate, and their limiting distribution can be expressed as a function of a random walk. A simulation is conducted to demonstrate the usefulness of this method by comparing the powers between the MIC and the Schwarz information criterion.

Related Topics
Physical Sciences and Engineering Mathematics Numerical Analysis