File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Asymptotic Null Distribution Of The Modified Likelihood Ratio Test For Homogeneity In Finite Mixture Models

TitleAsymptotic Null Distribution Of The Modified Likelihood Ratio Test For Homogeneity In Finite Mixture Models
Authors
Issue Date2018
PublisherElsevier.
Citation
Computational Statistics and Data Analysis, 2018, v. 127, p. 248-257 How to Cite?
AbstractLikelihood-based methods play a central role in statistical inference for parametric models. Among these, the modified likelihood ratio test is preferred in testing for homogeneity in finite mixture models. The test statistic is related to the maximum of a quadratic function under general regularity conditions. Re-parameterization is shown to have overcome the difficulty when linear independence is not satisfied. Models with parameter constraints are also considered. The asymptotic null distribution of the test statistic is shown to have a chi-bar-squared distribution in both constrained and unconstrained cases. We extend the result to linear models and demonstrate that the chi-bar-squared distribution is also applicable. The general asymptotic result provides a much simpler testing procedure with an exact form of the asymptotic distribution compared to re-sampling approach in the literature. It also offers accurate -value as shown in simulation. The results are checked by extensive simulation and are supplemented by a breast cancer data example.
Persistent Identifierhttp://hdl.handle.net/10722/259502
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWONG, TST-
dc.contributor.authorLam, KF-
dc.contributor.authorZHAO, VX-
dc.date.accessioned2018-09-03T04:08:52Z-
dc.date.available2018-09-03T04:08:52Z-
dc.date.issued2018-
dc.identifier.citationComputational Statistics and Data Analysis, 2018, v. 127, p. 248-257-
dc.identifier.urihttp://hdl.handle.net/10722/259502-
dc.description.abstractLikelihood-based methods play a central role in statistical inference for parametric models. Among these, the modified likelihood ratio test is preferred in testing for homogeneity in finite mixture models. The test statistic is related to the maximum of a quadratic function under general regularity conditions. Re-parameterization is shown to have overcome the difficulty when linear independence is not satisfied. Models with parameter constraints are also considered. The asymptotic null distribution of the test statistic is shown to have a chi-bar-squared distribution in both constrained and unconstrained cases. We extend the result to linear models and demonstrate that the chi-bar-squared distribution is also applicable. The general asymptotic result provides a much simpler testing procedure with an exact form of the asymptotic distribution compared to re-sampling approach in the literature. It also offers accurate -value as shown in simulation. The results are checked by extensive simulation and are supplemented by a breast cancer data example.-
dc.languageeng-
dc.publisherElsevier. -
dc.relation.ispartofComputational Statistics and Data Analysis-
dc.titleAsymptotic Null Distribution Of The Modified Likelihood Ratio Test For Homogeneity In Finite Mixture Models-
dc.typeArticle-
dc.identifier.emailLam, KF: hrntlkf@hkucc.hku.hk-
dc.identifier.authorityLam, KF=rp00718-
dc.identifier.doi10.1016/j.csda.2018.05.010-
dc.identifier.hkuros289165-
dc.identifier.volume127-
dc.identifier.spage248-
dc.identifier.epage257-
dc.identifier.isiWOS:000439748700016-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats