Estimation in a class of nonlinear heteroscedastic time series models
Statistics Theory
2008-02-08 v2 Statistics Theory
Abstract
Parameter estimation in a class of heteroscedastic time series models is investigated. The existence of conditional least-squares and conditional likelihood estimators is proved. Their consistency and their asymptotic normality are established. Kernel estimators of the noise's density and its derivatives are defined and shown to be uniformly consistent. A simulation experiment conducted shows that the estimators perform well for large sample size.
Keywords
Cite
@article{arxiv.0712.1673,
title = {Estimation in a class of nonlinear heteroscedastic time series models},
author = {Joseph Ngatchou-Wandji},
journal= {arXiv preprint arXiv:0712.1673},
year = {2008}
}
Comments
Published in at http://dx.doi.org/10.1214/07-EJS157 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)