Abstract
This paper is devoted to the goodness-of-fit test for the general autoregressive models in time series. By averaging for the weighted residuals, we construct a score type test which is asymptotically standard chi-squared under the null and has some desirable power properties under the alternatives. Specifically, the test is sensitive to alternatives and can detect the alternatives approaching, along a direction, the null at a rate that is arbitrarily close to n -1/2. Furthermore, when the alternatives are not directional, we construct asymptotically distribution-free maximin tests for a large class of alternatives. The performance of the tests is evaluated through simulation studies.
Original language | English |
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Pages (from-to) | 439-450 |
Number of pages | 12 |
Journal | Acta Mathematicae Applicatae Sinica |
Volume | 23 |
Issue number | 3 |
DOIs | |
Publication status | Published - Jul 2007 |
Scopus Subject Areas
- Applied Mathematics
User-Defined Keywords
- Autoregressive model
- Goodness-of-fit
- Maximin test
- Model checking
- Score type test
- Time series