Projected likelihood contrasts for testing homogeneity in finite mixture models with nuisance parameters
Abstract
This paper develops a test for homogeneity in finite mixture models where the mixing proportions are known a priori (taken to be 0.5) and a common nuisance parameter is present. Statistical tests based on the notion of Projected Likelihood Contrasts (PLC) are considered. The PLC is a slight modification of the usual likelihood ratio statistic or the Wilk's and is similar in spirit to the Rao's score test. Theoretical investigations have been carried out to understand the large sample statistical properties of these tests. Simulation studies have been carried out to understand the behavior of the null distribution of the PLC statistic in the case of Gaussian mixtures with unknown means (common variance as nuisance parameter) and unknown variances (common mean as nuisance parameter). The results are in conformity with the theoretical results obtained. Power functions of these tests have been evaluated based on simulations from Gaussian mixtures.
Keywords
Cite
@article{arxiv.0805.2460,
title = {Projected likelihood contrasts for testing homogeneity in finite mixture models with nuisance parameters},
author = {Debapriya Sengupta and Rahul Mazumder},
journal= {arXiv preprint arXiv:0805.2460},
year = {2008}
}
Comments
Published in at http://dx.doi.org/10.1214/193940307000000194 the IMS Collections (http://www.imstat.org/publications/imscollections.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)