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Bootstrapping regression quantiles
Authors:
M. Aerts a;
P. Janssen a;
N. Veraverbeke -
a
| Affiliation: | a Limburgs Universitair Centrum, Diepenbeek, Belgium |
DOI:
10.1080/10485259408832597
Publication Frequency:
8 issues per year
Subjects:
Mathematical Economics;
Mathematical Finance;
Medical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
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(English)
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Abstract
Consider the fixed design heteroscedastic regression model
 where μ(.) and σ(.) are unknown smooth functions and ηi, i=1,…,n are i.i.d. random variables. We introduce a new resampling method for this nonparametric regression model and establish the asymptotic consistency of the bootstrap approximation for Stone's (1977) kernel estimator for Fx(y), the d.f. of the response y for a given value of x, and Cheng's (1984) regression quantile estimator for μ(x).
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| Keywords: Bootstrap approximation; fixed design; heteroscedastic model; kernel estimator; nonparametric regression; regression quantiles |
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