Exponential Bounds of Mean Error for the Kernal Estimates of Regression Functions.

Abstract

Let (X,Y), (X sub 1, Y sub 1),...,(X sub n, Y sub n) be i.i.d. R sub L x R-valued random vectors with E/Y/e infinity, and let Q sub n be a kernel estimate of the regression function Q(x) = E(Y/X = x). This paper establishes an exponential bound of the mean deviation between Q sub n and Q(x) given the training sample Z sub n = (X sub 1, Y sub 1), ...,X sub n, Y sub n), under the conditions as weak as possible. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1985
Accession Number
ADA167345

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  • L. C. Zhao

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  • University of Pittsburgh

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