Large sample properties of parameter least squares estimates for time-varying ARMA models

Christian Francq; Antony Gautier

doi:10.1111/j.1467-9892.2004.02003.x

Large sample properties of parameter least squares estimates for time-varying ARMA models

Christian Francq
, Antony Gautier

Université de Lille

Résultats de recherche: Contribution à un journal › Article › Revue par des pairs

Résumé

This paper considers estimation of ARMA models with time-varying coefficients. The ARMA parameters belong to d different regimes. The changes in regime occur at irregular time intervals. Consistency and asymptotic normality of least squares and quasi-generalized least squares estimators are shown.

langue originale	Anglais
Pages (de - à)	765-783
Nombre de pages	19
journal	Journal of Time Series Analysis
Volume	25
Numéro de publication	5
Les DOIs	https://doi.org/10.1111/j.1467-9892.2004.02003.x
état	Publié - 1 sept. 2004
Modification externe	Oui

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10.1111/j.1467-9892.2004.02003.x

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title = "Large sample properties of parameter least squares estimates for time-varying ARMA models",

abstract = "This paper considers estimation of ARMA models with time-varying coefficients. The ARMA parameters belong to d different regimes. The changes in regime occur at irregular time intervals. Consistency and asymptotic normality of least squares and quasi-generalized least squares estimators are shown.",

keywords = "Asymptotic normality, Consistency, Non-stationary processes, Quasi-generalized least squares estimator, Time-varying models",

author = "Christian Francq and Antony Gautier",

year = "2004",

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AU - Gautier, Antony

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KW - Asymptotic normality

KW - Consistency

KW - Non-stationary processes

KW - Quasi-generalized least squares estimator

KW - Time-varying models

U2 - 10.1111/j.1467-9892.2004.02003.x

DO - 10.1111/j.1467-9892.2004.02003.x

M3 - Article

AN - SCOPUS:3943108820

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JO - Journal of Time Series Analysis

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Large sample properties of parameter least squares estimates for time-varying ARMA models

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