An Introduction to Kernel and Nearest-Neighbor Nonparametric RegressionNaomi Altman|The American Statistician|1992 Abstract Nonparametric regression is a set of techniques for estimating a regression curve without making strong assumptions about the shape of the true regression function. These techniques are therefore useful for building and checking parametric models, as well as for data description. Kernel and nearest-neighbor regression estimators are local versions of univariate location estimators, and so they can readily be introduced to beginning students and consulting clients who are familiar with such summaries as the sample mean and median.
An Introduction to Kernel and Nearest-Neighbor Nonparametric RegressionNaomi Altman|The American Statistician|1992 Nonparametric regressiOn 1s a set of techniques for estimating a regression curve without making strong assumptions about the shape of the true regression function.These techniques are therefore useful for building and checking parametric models, as well as for data description.Kernel and nearest neighbor regression estimators are local versions of univariate location estimators, and so they can readily be introduced to beginning students, and consulting clients who are familiar with such summaries as the sample mean and median.