Estimating the integral of a squared regression function with Latin hypercube sampling

Wei-Liem Loh

Statistics & Probability Letters, 1997, vol. 31, issue 4, 339-349

Abstract: This article is concerned with the estimation of the integral of a squared regression function using Latin hypercube sampling. A class of generalized nearest-neighbour estimators is proposed and their properties are investigated with respect to various smoothness classes of regression functions. In particular, mild conditions are established which ensure that achieves a root-n convergence rate. It is further shown that has an asymptotic mean squared error smaller than that of any regular estimator based on an i.i.d. sample of the same size.

Keywords: Integrated; squared; regression; function; Latin; hypercube; sampling; Nearest; neighbour; estimator; Nonparametric; information; bound; Rate; of; convergence (search for similar items in EconPapers)
Date: 1997
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