We consider nonparametric estimation of mean regression and conditional variance (or volatility) functions in nonlinear stochastic regression models. Simultaneous confidence bands are constructed and the coverage probabilities are shown to be asymptotically correct. The imposed dependence structure allows applications in many linear and nonlinear auto-regressive processes. The results are applied to the S&P 500 Index data.
Publié le : 2008-08-15
Classification:
Long-range dependence,
model validation,
moderate deviation,
nonlinear time series,
nonparametric regression,
short-range dependence,
62G08,
62G15
@article{1216237302,
author = {Zhao, Zhibiao and Wu, Wei Biao},
title = {Confidence bands in nonparametric time series regression},
journal = {Ann. Statist.},
volume = {36},
number = {1},
year = {2008},
pages = { 1854-1878},
language = {en},
url = {http://dml.mathdoc.fr/item/1216237302}
}
Zhao, Zhibiao; Wu, Wei Biao. Confidence bands in nonparametric time series regression. Ann. Statist., Tome 36 (2008) no. 1, pp. 1854-1878. http://gdmltest.u-ga.fr/item/1216237302/