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Flexible Parsimonious Smoothing and Additive Modeling

Jerome H. Friedman and Bernard W. Silverman
Technometrics
Vol. 31, No. 1 (Feb., 1989), pp. 3-21
DOI: 10.2307/1270359
Stable URL: http://www.jstor.org/stable/1270359
Page Count: 19
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Flexible Parsimonious Smoothing and Additive Modeling
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Abstract

A simple method is presented for fitting regression models that are nonlinear in the explanatory variables. Despite its simplicity-or perhaps because of it-the method has some powerful characteristics that cause it to be competitive with and often superior to more sophisticated techniques, especially for small data sets in the presence of high noise.

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