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Diagnostic tests for the distribution of random effects in multivariate mixed effects model

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dc.contributor.authorMeintanis, Simos G.
dc.contributor.authorAllison, James S.
dc.contributor.authorSantana, Leonard
dc.contributor.researchID21262977 - Meintanis, Simos George
dc.contributor.researchID11985682 - Allison, James Samuel
dc.contributor.researchID11803371 - Santana, Leonard
dc.date.accessioned2017-04-13T09:00:47Z
dc.date.available2017-04-13T09:00:47Z
dc.date.issued2016
dc.description.abstractFourier methods are proposed for testing the distribution of random effects in classical and robust multivariate mixed effects models. The test statistics involve estimation of the characteristic function of random effects. Theoretical and computational issues are addressed while Monte Carlo results show that the new procedures compare favorably with other methodsen_US
dc.identifier.citationMeintanis, S.G. et al. 2016. Diagnostic tests for the distribution of random effects in multivariate mixed effects model. Communications in statistics. Theory and methods, 45(1):201-215. [https://doi.org/10.1080/03610926.2013.828073]en_US
dc.identifier.issn0361-0926
dc.identifier.issn1532-415X (Online)
dc.identifier.urihttp://hdl.handle.net/10394/21392
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/03610926.2013.828073
dc.identifier.urihttps://doi.org/10.1080/03610926.2013.828073
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectEmpirical characteristic functionen_US
dc.subjectGoodness-of-fit testen_US
dc.subjectMixed effects modelen_US
dc.titleDiagnostic tests for the distribution of random effects in multivariate mixed effects modelen_US
dc.typeArticleen_US

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