Journal
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
Volume 50, Issue 3, Pages 1034-1046Publisher
WILEY
DOI: 10.1002/cjs.11651
Keywords
Chi-square; contaminated mixture model; EM-test; homogeneity; limiting distribution
Categories
Funding
- National Natural Science Foundation of China [11801359, 11971300, 11771144, 11771145, 11901519]
- Natural Science Foundation of Shanghai [19ZR1420900]
- Natural Sciences and Engineering Research Council of Canada [RGPIN-2018-05846]
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Contaminated mixture models (CMMs) have wide applications in the real world. An EM-test has been developed for testing homogeneity in CMMs, with demonstrated excellent finite-sample performance through simulation studies. Two real-data examples illustrate the applications of the proposed method.
Contaminated mixture models (CMMs) have wide applications in the real world. Testing homogeneity in CMMs is an important and fundamental problem. In this article, we develop an EM-test for homogeneity in the general framework of the CMM with unbounded likelihood. The null limiting distribution of the test is shown to be a shifted mixture of chi-square distributions. Simulation studies demonstrate that the EM-test has excellent finite-sample performance. Two real-data examples illustrate the applications of the proposed method.
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