Abstract
In classical statistics, regression means linear regression. Recently, more flexible regression tools have been developed, that exploit the dramatic increase in computing power and speed. In this paper we describe some of these developments. The main background reference is Hastie and Tibshirani (1990).
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References
Friedman, J. (1991), Multivariate adaptive regression splines (with discussion)’, Annals of Statistics 19(1), 1–141.
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Hastie, T. & Tibshirani, R. (1990), Generalized Additive Models, Chapman and Hall.
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© 1994 Springer-Verlag Berlin Heidelberg
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Hastie, T.J., Tibshirani, R.J. (1994). Nonparametric Regression and Classification Part I—Nonparametric Regression. In: Cherkassky, V., Friedman, J.H., Wechsler, H. (eds) From Statistics to Neural Networks. NATO ASI Series, vol 136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79119-2_2
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DOI: https://doi.org/10.1007/978-3-642-79119-2_2
Publisher Name: Springer, Berlin, Heidelberg
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