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Abstract:
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A general expository description is given of the use of quadratic inference function. This methodology allows one to do efficient estimation and hypothesis testing in a semiparametric model defined by a set of mean-zero estimating functions. The inference function is related to a quadratic minimum distance problem, and the asymptotic chi-squared properties are shown to be the consequences of asymptotic projection properties. This talk will provide an overview of the quadratic inference function on model selection, moment selection and mixed-effects modeling to fully utilize the correlated nature of the data.
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