Analysis of clustered data using Tweedie models with covariate-dependent random effects

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dc.contributor.advisorRenjun Ma
dc.contributor.advisorHasan, Tariqul
dc.contributor.authorIslam, MD Dedarul
dc.date.accessioned2023-03-01T16:19:10Z
dc.date.available2023-03-01T16:19:10Z
dc.date.issued2013
dc.date.updated2023-03-01T15:01:31Z
dc.description.abstractClustered data are traditionally handled using models with covariate-independent random effects in the statistical community. Models with covariatedependent random effects have recently gained attention. In this thesis, we discuss the application of Tweedie models with covariate-dependent random effects proposed by Ma (1999). Tweedie models with covariate-dependent random effects are applied to analyses of count, continuous and semi-continuous data from transportation, education and health studies. Tweedie models with covariate-dependent random effects have flexible parametric interpretation for multilevel data since the cluster-specific covariates can be incorporated into random effects. Similar to Tweedie models with covariate-independent random effects, the parameter estimation and random effect prediction of Tweedie models with covariate-dependent random effects can also be done using the orthodox best linear unbiased predictor (BLUP) approach which does not require inverse calculation of large covariance matrices; therefore it is in general computationally efficient. On the basis of simulations and worked examples, we illustrated that Tweedie models with covariate-dependent random effects are useful for situations where the clustering effects are likely influenced by covariates at the relevant cluster levels.
dc.description.copyright© MD Dedarul Islam, 2013
dc.formattext/xml
dc.format.extentxv, 125 pages
dc.format.mediumelectronic
dc.identifier.oclc(OCoLC)1333708234en
dc.identifier.otherThesis 9147en
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/13482
dc.language.isoen_CA
dc.publisherUniversity of New Brunswick
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineMathematics and Statistics
dc.subject.lcshStatistics.en
dc.subject.lcshCluster analysis.en
dc.subject.lcshData sets.en
dc.titleAnalysis of clustered data using Tweedie models with covariate-dependent random effects
dc.typemaster thesis
thesis.degree.disciplineMathematics and Statistics
thesis.degree.fullnameMaster of Science
thesis.degree.grantorUniversity of New Brunswick
thesis.degree.levelmasters
thesis.degree.nameM.Sc.

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