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The null distribution of the likelihood ratio test for a mixture of two normals after a restricted box-cox transformation

 

作者: Yuming Ning,   Stephen J. Finch,  

 

期刊: Communications in Statistics - Simulation and Computation  (Taylor Available online 2000)
卷期: Volume 29, issue 2  

页码: 449-461

 

ISSN:0361-0918

 

年代: 2000

 

DOI:10.1080/03610910008813621

 

出版商: Marcel Dekker, Inc.

 

关键词: randomly selected starting points;variable metric minimization

 

数据来源: Taylor

 

摘要:

Macleanet al.(1976) applied a specific Box-Cox transformation to test for mixtures of distributions against a single distribution. Their null hypothesis is that a sample ofnobservations is from a normal distribution with unknown mean and variance after a restricted Box-Cox transformation. The alternative is that the sample is from a mixture of two normal distributions, each with unknown mean and unknown, but equal, variance after another restricted Box-Cox transformation. We developed a computer program that calculated the maximum likelihood estimates (MLEs) and likelihood ratio test (LRT) statistic for the above. Our algorithm for the calculation of the MLEs of the unknown parameters used multiple starting points to protect against convergence to a local rather than global maximum. We then simulated the distribution of the LRT for samples drawn from a normal distribution and five Box-Cox transformations of a normal distribution. The null distribution appeared to be the same for the Box-Cox transformations studied and appeared to be distributed as a chi-square random variable for samples of 25 or more. The degrees of freedom parameter appeared to be a monotonically decreasing function of the sample size. The null distribution of this LRT appeared to converge to a chi-square distribution with 2.5 degrees of freedom. We estimated the critical values for the 0.10, 0.05, and 0.01 levels of significance.

 

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