Probabilities of maximal deviations for nonparametric regression function estimates

Gordon J. Johnston

Journal of Multivariate Analysis, 1982, vol. 12, issue 3, 402-414

Abstract: Let (X, Y) have regression function m(x) = E(Y X = x), and let X have a marginal density f1(x). We consider two nonparameteric estimates of m(x): the Watson estimate when f1 is known and the Yang estimate when f1 is known or unknown. For both estimates the asymptotic distribution of the maximal deviation from m(x) is proved, thus extending results of Bickel and Rosenblatt for the estimation of density functions.

Keywords: Density; estimates; nonparemetric; regression; estimates; maximal; deviations; Gaussian; processes (search for similar items in EconPapers)
Date: 1982
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Citations: View citations in EconPapers (33)

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