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  • Application and computation of likelihood methods for regression with measurement error

    Creator:
    Higdon, Roger
    Abstract:
    This thesis advocates the use of maximum likelihood analysis for generalized regression models with measurement error in a single explanatory variable. This will be done first by presenting a computational algorithm and the numerical details for carrying out this algorithm on a wide variety of models. The computational methods will...
    Resource Type:
    Dissertation
    Full Text:
    computational methods will be based on the EM algorithm in conjunction with the use of Gauss-Hermite quadrature

  • Laplace approximations to likelihood functions for generalized linear mixed models

    Creator:
    Liu, Qing, 1961-
    Abstract:
    This thesis considers likelihood inferences for generalized linear models with additional random effects. The likelihood function involved ordinarily cannot be evaluated in closed form and numerical integration is needed. The theme of the thesis is a closed-form approximation based on Laplace's method. We first consider a special yet important case...
    Resource Type:
    Dissertation
    Full Text:
    the end of this section, formula (2.8) is based on inte- grating a Gaussian density which