Second-order least squares estimation in regression models with application to measurement error problems

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dc.contributor.authorAbarin, Taraneh
dc.contributor.examiningcommitteeJohn Brewster (Statistics), James Fu (Statistics), Gady Jacoby (Asper School of Business), Julie Zhou (Mathematics and Statistics, University of Victoria)en
dc.contributor.supervisorWang, Liqun (Statistics)en
dc.date.accessioned2009-01-21T15:17:56Z
dc.date.available2009-01-21T15:17:56Z
dc.date.issued2009-01-21T15:17:56Z
dc.degree.disciplineStatisticsen_US
dc.degree.levelDoctor of Philosophy (Ph.D.)en_US
dc.description.abstractThis thesis studies the Second-order Least Squares (SLS) estimation method in regression models with and without measurement error. Applications of the methodology in general quasi-likelihood and variance function models, censored models, and linear and generalized linear models are examined and strong consistency and asymptotic normality are established. To overcome the numerical difficulties of minimizing an objective function that involves multiple integrals, a simulation-based SLS estimator is used and its asymptotic properties are studied. Finite sample performances of the estimators in all of the studied models are investigated through simulation studies.en
dc.description.noteFebruary 2009en
dc.format.extent659093 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.citationAbarin, T. and Wang, L. (2009). Second-Order Least Squares Estimation of Censored Regression Models. J. STAT. Plan. Infer. 139, 125-135.en
dc.identifier.citationAbarin, T. and Wang, L. (2006). Comparison of GMM with Second-order Least Squares Estimation in Nonlinear Models. Far East J. Theo. Stat. 20 (2), 179 -- 196.en
dc.identifier.urihttp://hdl.handle.net/1993/3126
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectNonlinear regressionen
dc.subjectCensored regression model
dc.subjectGeneralized linear models
dc.subjectMeasurement error
dc.subjectConsistency
dc.subjectAsymptotic normality
dc.subjectLeast squares method
dc.subjectMethod of moments
dc.subjectHeterogeneity
dc.subjectInstrumental variable
dc.subjectSimulation-based estimation
dc.titleSecond-order least squares estimation in regression models with application to measurement error problemsen
dc.typedoctoral thesisen_US
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