Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1146831 | Journal of Multivariate Analysis | 2006 | 21 Pages |
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