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Testing for a finite mixture model with two components
Authors:Hanfeng Chen  Jiahua Chen   John D. Kalbfleisch
Affiliation:Bowling Green State University, USA; University of Waterloo, Canada
Abstract:Summary.  We consider a finite mixture model with k components and a kernel distribution from a general one-parameter family. The problem of testing the hypothesis k =2 versus k 3 is studied. There has been no general statistical testing procedure for this problem. We propose a modified likelihood ratio statistic where under the null and the alternative hypotheses the estimates of the parameters are obtained from a modified likelihood function. It is shown that estimators of the support points are consistent. The asymptotic null distribution of the modified likelihood ratio test proposed is derived and found to be relatively simple and easily applied. Simulation studies for the asymptotic modified likelihood ratio test based on finite mixture models with normal, binomial and Poisson kernels suggest that the test proposed performs well. Simulation studies are also conducted for a bootstrap method with normal kernels. An example involving foetal movement data from a medical study illustrates the testing procedure.
Keywords:Binomial mixture    Finite mixture model    Likelihood ratio test    Non-regular estimation    Normal mixture    Penalty    Poisson mixture    Strong identifiability
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