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Nonlinear regression checking via local polynomial smoothing with applications to thermogravimetric analysis
Author(s) -
Cao Ricardo,
Naya Salvador
Publication year - 2009
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1227
Subject(s) - polynomial regression , goodness of fit , nonlinear regression , statistic , polynomial , local regression , nonlinear system , nonparametric regression , test statistic , logistic regression , mathematics , parametric statistics , statistics , regression analysis , smoothing , nonparametric statistics , computer science , statistical hypothesis testing , mathematical analysis , physics , quantum mechanics
A goodness‐of‐fit test statistic for nonlinear regression models based on local polynomial estimation is proposed in this paper. The criterion used to construct the test is the distance between the parametric fit and the nonparametric regression estimation. The good performance of the test is shown via a simulation study. The method is applied to check a logistic mixture regression model for real data coming from a thermal analysis problem. Copyright © 2009 John Wiley & Sons, Ltd.