Optimal designs for nonparametric kernel regression

Hans-Georg Müller

Statistics & Probability Letters, 1984, vol. 2, issue 5, 285-290

Abstract: We consider the fixed design regression model Yi = g(ti) + [xi]i, I = 1, ..., n, where [xi]i are (not necessarily i.i.d.) no variables, ti constitute the design points where nonrepeatable measurements are to be taken and Yi are the observations from which g and its derivatives are to be estimated. The dependency of the Integrated Mean Squared Error of two different types of kernel estimates on the design {t1, ..., tn} is established. This allows the derivation of asymptotically optimal designs.

Keywords: nonparametric; regression; fixed; design; design; density; kernel; estimates; of; derivatives; locally; varying; bandwidth (search for similar items in EconPapers)
Date: 1984
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