Testing goodness of fit of polynomial models via spline smoothing techniques
AbstractA new test statistic is proposed for testing goodness of fit of an mth order polynomial regression model. The test statistic is [integral operator]10[[mu](m)[lambda](t)]2 dt, where [mu](m)[lambda] is the mth order derivative of a 2mth order smoothing spline estimator for the regression function [mu] and [lambda] is its associated smoothing parameter. The large sample properties of the test statistic are derived under both the null hypothesis and local alternatives. A numerical example is included that illustrates the technique.
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Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 19 (1994)
Issue (Month): 1 (January)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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- Chin-Shang Li, 2012. "Testing for no effect via splines," Computational Statistics, Springer, vol. 27(2), pages 343-357, June.
- Emmanuel Guerre & Pascal Lavergne, 2004. "Data-Driven Rate-Optimal Specification Testing In Regression Models," Econometrics 0411008, EconWPA.
- Emmanuel Guerre & Pascal Lavergne, 2001. "Rate-optimal data-driven specification testing in regression models," Econometrics 0107001, EconWPA.
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