Cluster-based lack of fit tests for nonlinear regression models

Cluster-based lack of fit tests for nonlinear regression models

Doctor of Philosophy === Department of Statistics === James W. Neill === Checking the adequacy of a proposed parametric nonlinear regression model is important in order to obtain useful predictions and reliable parameter inferences. Lack of fit is said to exist when the regression function does n...

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Bibliographic Details
Main Author: Munasinghe, Wijith Prasantha
Language:en_US
Published: Kansas State University 2010
Subjects:
Nonlinear regression models
Lack of fit tests
Cluster-based
Maximin clustering
Non-central Chi-Square distribution
Likelihood ratio tests
Mathematics (0405)
Statistics (0463)
Online Access:http://hdl.handle.net/2097/2366

Internet

http://hdl.handle.net/2097/2366

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