Splines, Smoothers, and Kernels

作者: Richard A. Berk

DOI: 10.1007/978-3-319-44048-4_2

关键词:

摘要: In this chapter, we begin the transition from conventional regression analysis to statistical learning. Some of procedures discussed have primarily a didactic purpose, but some can be effective data tools as well. Regression splines are an example former. Smoothing latter. The “wrong model” perspective is adopted for all level II with regularization introduced key estimation feature. Kernels that will play essential role in later chapters also introduced.

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