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A note on variable selection in nonparametric regression with dependent data

✍ Scribed by Wenceslao González-Manteiga; Alejandro Quintela-del-Rı́o; Philippe Vieu

Publisher
Elsevier Science
Year
2002
Tongue
English
Weight
128 KB
Volume
57
Category
Article
ISSN
0167-7152

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✦ Synopsis

We develop a nonparametric test, based on kernel smoothers, in order to decide whether some covariates could be suppressed in a multidimensional nonparametric regression study. We give the asymptotic distribution of the statistic involved in our test, under a general dependence assumption on the sample that allows for application to time series prediction.

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