Penalized splines and reproducing kernel methods

American Statistical Association
Publication Type:
Journal Article
The American Statistician, 2006, 60 (3), pp. 233 - 240
Issue Date:
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Two data analytic research areaspenalized splines and reproducing kernel methodshave become very vibrant since the mid-1990s. This article shows how the former can be embedded in the latter via theory for reproducing kernel Hilbert spaces. This connection facilitates cross-fertilization between the two bodies of research. In particular, connections between support vector machines and penalized splines are established. These allow for significant reductions in computational complexity, and easier incorporation of special structure such as additivity.
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