Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1148379 | Journal of Statistical Planning and Inference | 2009 | 20 Pages |
Abstract
We consider several procedures to detect changes in the mean or the covariance structure of a linear process. The tests are based on the weighted CUSUM process. The limit distributions of the test statistics are derived under the no change null hypothesis. We develop new strong and weak approximations for the sample mean as well as the sample correlations of linear processes. A small Monte Carlo simulation illustrates the applicability of our results.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
István Berkes, Edit Gombay, Lajos Horváth,