Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems

Peter Hall

Journal of Multivariate Analysis, 1990, vol. 32, issue 2, 177-203

Abstract: We describe a bootstrap method for estimating mean squared error and smoothing parameter in nonparametric problems. The method involves using a resample of smaller size than the original sample. There are many applications, which are illustrated using the special cases of nonparametric density estimation, nonparametric regression, and tail parameter estimation.

Keywords: bias; bootstrap; density; estimation; mean; squared; error; nonparametric; regression; smoothing; parameter (search for similar items in EconPapers)
Date: 1990
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Citations: View citations in EconPapers (104)

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