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Regression Splines

Regression splines model a nonlinear relationship by fitting piecewise polynomials that join smoothly at a set of points called knots. Cubic and natural splines are the most common, and smoothing splines add a roughness penalty that automatically balances fit against smoothness. Splines are the standard flexible building block for univariate nonlinear regression and the basis of generalized additive models.

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Regression and Smoothing Splines

Taksonomisk metoderegister · ml-model / machine-learning

Eilers, P. H. C., & Marx, B. D. (1996). Flexible smoothing with B-splines and penalties. Statistical Science, 11(2), 89–121. · DOI 10.1214/ss/1038425655
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning (2nd ed.). Springer. · ISBN 978-0-387-84857-0

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Same method familyGeneralized Additive Modelmachine-suggested · Relational suggestion, not evidence.Same method familyLOESSmachine-suggested · Relational suggestion, not evidence.Same method familyMARSmachine-suggested · Relational suggestion, not evidence.See alsoPolynomial Regressionmachine-suggested · Relational suggestion, not evidence.