Please use this identifier to cite or link to this item:
Title: Sub-sampling and weighting approaches to model checking
Keywords: Estimating equation; Lack of fit test; Maximum likelihood estimation;
Issue Date: 5-Oct-2003
Citation: 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.
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
LiCW.pdf564.54 kBAdobe PDF



Page view(s)

checked on Nov 17, 2018


checked on Nov 17, 2018

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.