CHANGE‐POINT DETECTION WITH RANK STATISTICS IN LONG‐MEMORY TIME‐SERIES MODELS |
| |
| Authors: | Lihong Wang |
| |
| Affiliation: | Department of Mathematics, Institute of Mathematical Science, Nanjing University, Nanjing, 210093, China. e‐mail: |
| |
| Abstract: | Wilcoxon‐type rank statistics are considered for testing a long‐memory time‐series model with a common distribution against the alternatives involving a change in the distribution at an unknown time point. The asymptotic properties of the test statistics and the change‐point estimators are studied. Finite‐sample behaviours are investigated in a small Monte Carlo simulation study. Data examples from hydrology and telecommunications illustrate the method. |
| |
| Keywords: | change‐point analysis long‐memory process rank statistics |
|
|
