Open Access
2008 Estimation in a class of nonlinear heteroscedastic time series models
Joseph Ngatchou-Wandji
Electron. J. Statist. 2: 40-62 (2008). DOI: 10.1214/07-EJS157

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.

Citation

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Joseph Ngatchou-Wandji. "Estimation in a class of nonlinear heteroscedastic time series models." Electron. J. Statist. 2 40 - 62, 2008. https://doi.org/10.1214/07-EJS157

Information

Published: 2008
First available in Project Euclid: 1 February 2008

zbMATH: 1135.62369
MathSciNet: MR2386085
Digital Object Identifier: 10.1214/07-EJS157

Subjects:
Primary: 62M10
Secondary: 62F12

Keywords: Conditional least-squares estimation , Conditional likelihood estimation , Heteroscedastic models , kernel density estimation , LaTeX2e

Rights: Copyright © 2008 The Institute of Mathematical Statistics and the Bernoulli Society

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