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Generalized Autoregressive (GAR) Model: A Comparison of Maximum Likelihood and Whittle Estimation Procedures Using a Simulation Study.


Citation

Shitan, Mahendran and Peiris, Shelton (2008) Generalized Autoregressive (GAR) Model: A Comparison of Maximum Likelihood and Whittle Estimation Procedures Using a Simulation Study. Communications in Statistics: Simulation and Computation, 37 (3). pp. 560-570. ISSN 0361-0918; ESSN: 1532-4141

Abstract

This article evaluates the performance of two estimators namely, the Maximum Likelihood Estimator (MLE) and Whittle's Estimator (WE), through a simulation study for the Generalised Autoregressive (GAR) model. As expected, it is found that for the parameters and σ2, the MLE and WE have a better performance than Method of Moments (MOM) estimator. For the parameter δ, MOM sometimes appears to have a slightly better performance than MLE and WE, possibly due to truncation approximations associated with the hypergeometric functions for calculating the autocorrelation function. However, the MLE and WE can be used in practice without loss of efficiency.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
DOI Number: https://doi.org/10.1080/03610910701649598
Publisher: Taylor & Francis
Keywords: Generalised autoregressive (GAR) process,Method of moments estimates; Maximum likelihood estimates,Simulation, Whittle’s estimates.
Depositing User: Najwani Amir Sariffudin
Date Deposited: 02 Jun 2010 02:30
Last Modified: 29 Oct 2014 07:27
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1080/03610910701649598
URI: http://psasir.upm.edu.my/id/eprint/7027
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