Displaying similar documents to “A classification of nonlinear regression models and parameter confidence regions”

Confidence regions in nonlinear regression models

Rastislav Potocký, Van Ban To (1992)

Applications of Mathematics

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New curvature measures for nonlinear regression models are developed and methods of their computing are given. Using these measures, more accurate confidence regions for parameters than those based on linear or quadratic approximations are obtained.

How to deal with regression models with a weak nonlinearity

Eva Tesaríková, Lubomír Kubáček (2001)

Discussiones Mathematicae Probability and Statistics

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If a nonlinear regression model is linearized in a non-sufficient small neighbourhood of the actual parameter, then all statistical inferences may be deteriorated. Some criteria how to recognize this are already developed. The aim of the paper is to demonstrate the behaviour of the program for utilization of these criteria.

Selection in parametric models via some stepdown procedures

Konrad Furmańczyk (2014)

Applicationes Mathematicae

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The paper considers the problem of consistent variable selection in parametic models with the use of stepdown multiple hypothesis procedures. Our approach completes the results of Bunea et al. [J. Statist. Plann. Inference 136 (2006)]. A simulation study supports the results obtained.