FINAL YEAR PROJECT'S AND GUIDANCE

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Statistical Inference Based On Estimating Functions in Exact and Misspecified Models Posted: 01 Nov 2009 06:22 PM PST Estimating functions, introduced by Godambe, are a useful tool for constructing estimators. The classical maximum likelihood estimator and the method of moments estimator are special cases of estimators generated as the solution to certain estimating equations.The main advantage of this method is that it does not require knowledge of the full model, but rather of some functionals, such as a number of moments. We define an estimating function Ψ to be a Fisher estimating function if it satisfies Eθ(ΨΨTθ(dΨ/dθ). The motivation for considering this class of estimating functions is that a Fisher estimating function behaves much like the Fisher score, and the estimators generated as solutions to these estimating equations behave much like maximum likelihood estimators. Author:-Janicki, Ryan Louis University:- The University of Maryland DIRECT DOWNLOAD

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