The problem of testing the correctness of a nonlinear response function against unspecified general alternatives is considered. The proposed test statistic is a modification of a nonlinear analogue to the well-known linear regression lack-of-fit test and can be used with or without replication. Asymptotically valid critical points can be obtained from a central F-distribution. Also, when the null model is the orthogonal projection of the true model, the test statistic is asymptotically comparable to a random variable with a noncentral F-distribution.
CITATION STYLE
Neill, J. W. (2007). Testing for Lack of Fit in Nonlinear Regression. The Annals of Statistics, 16(2). https://doi.org/10.1214/aos/1176350831
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