Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/13570
Title: Sub-sampling and weighting approaches to model checking
Authors: LI CHENWEI
Keywords: Estimating equation; Lack of fit test; Maximum likelihood estimation;
Issue Date: 5-Oct-2003
Source: LI CHENWEI (2003-10-05). Sub-sampling and weighting approaches to model checking. ScholarBank@NUS Repository.
Abstract: Motivated by the ideas of sub-sampling and sample splitting, we propose a weighting approach to model checking that exploits the systematic differences under model misspecification between the weighted, the complementarily weighted and the unweighted parameter estimates. Standard error formulae for the differences are derived and the resulting standardized differences can be used to test the adequacy of the postulated model. Unlike many tests in the literature that are designed to test the goodness of fit of a particular class of models such as logistic regression, the proposed approach is very general and can be implemented easily to test the goodness of fit of any parametric model.
URI: http://scholarbank.nus.edu.sg/handle/10635/13570
Appears in Collections:Master's Theses (Open)

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