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Testing Parameter Change in General Integer‐Valued Time Series
Author(s) -
Diop Mamadou Lamine,
Kengne William
Publication year - 2017
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/jtsa.12240
Subject(s) - mathematics , test statistic , exponential family , estimator , series (stratigraphy) , null distribution , asymptotic distribution , statistics , statistical hypothesis testing , statistic , null hypothesis , paleontology , biology
We consider the structural change in a class of discrete valued time series, which the conditional distribution belongs to the one‐parameter exponential family. We propose a change point test based on the maximum likelihood estimator of the model's parameter. Under the null hypothesis (of no change), the test statistic converges to a well‐known distribution, allowing the calculation of the critical value of the test. The test statistic diverges to infinity under the alternative, meaning that the test has asymptotic power one. Some simulation results and real data applications are reported to show the effectiveness of the proposed procedure.