Mathematical Sciences: Generalized Linear Models

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The ability to describe complex bodies of data by mathematical models is an essential and challenging task. The investigator of this award expands the horizon for model fitting. The work on generalized model fitting is expected to have great impact on data analysis. The investigation will consider the estimation of nuisance dispersion parameters by partially Bayes methods. It will also examine the relationship between the adjusted profile likelihood and the modified profile likelihood methods.