STRONG CONSISTENCY OF THE LEAST SQUARES ESTIMATOR FOR A NON-ERGODIC THRESHOLD AUTOREGRESSIVE MODEL

Dinh Tuan Pham; K. S. Chan; Howell Tong

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STRONG CONSISTENCY OF THE LEAST SQUARES ESTIMATOR FOR A NON-ERGODIC THRESHOLD AUTOREGRESSIVE MODEL

Journal article

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STRONG CONSISTENCY OF THE LEAST SQUARES ESTIMATOR FOR A NON-ERGODIC THRESHOLD AUTOREGRESSIVE MODEL

Dinh Tuan Pham, K. S. Chan and Howell Tong

Statistica Sinica, Vol.1(2), pp.361-369

07/01/1991

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Abstract

We have shown that the least squares estimator for a non-ergodic, first order, self-exciting, threshold autoregressive model is strongly consistent under quite general conditions.

Autoregressive models

Consistent estimators

Ergodic theory

Estimators

Infinity

Least squares

Markov chains

Martingales

Nonlinear Time Series

Parametric models

Random variables

Details

Title: Subtitle: STRONG CONSISTENCY OF THE LEAST SQUARES ESTIMATOR FOR A NON-ERGODIC THRESHOLD AUTOREGRESSIVE MODEL
Creators: Dinh Tuan Pham
K. S. Chan
Howell Tong
Resource Type: Journal article
Publication Details: Statistica Sinica, Vol.1(2), pp.361-369
Publisher: Institute of Statistical Science, Academia Sinica and International Chinese Statistical Association
ISSN: 1017-0405
eISSN: 1996-8507
Language: English
Date published: 07/01/1991
Academic Unit: Statistics and Actuarial Science; Radiology
Record Identifier: 9984257733702771

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