Time series properties of the class of generalized first order autoregressive processes with moving average errors

Shitan, Mahendran and Shelton, Peiris (2011) Time series properties of the class of generalized first order autoregressive processes with moving average errors. Communications in Statistics-Theory and Methods, 40 (13). pp. 2259-2275. ISSN 0361-0926

Full text not available from this repository.

Abstract

A new class of time series models known as of order one with first order moving average errors has been introduced in order to reveal some hidden features of certain time series data. The variance and autocovariance of the process is derived in order to study the behaviour of the process. It is shown that in special cases these new results reduce to the standard ARMA results. Estimation of parameters based on the Whittle procedure is discussed. We illustrate the use of this class of model by using two examples

Item Type:Article
Keyword:Autoregression; Moving average; Errors; Autocorrelations; Variance; Autocovariance; Spectral density; Estimation; Time series; Fractional differencing; Long memory; Estimation
Subject:Autoregression (Statistics)
Subject:Time-series analysis
Subject:Mathematical statistics
Faculty or Institute:Faculty of Science
Publisher:Taylor&Francis
DOI Number:10.1080/03610921003765784
Altmetrics:http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1080/03610921003765784
ID Code:17418
Deposited By: Najwani Amir Sariffudin
Deposited On:23 Apr 2012 09:04
Last Modified:29 Oct 2012 02:22

Repository Staff Only: Edit item detail


Universiti Putra Malaysia Institutional Repository

Universiti Putra Malaysia Institutional Repository is an on-line digital archive that serves as a central collection and storage of scientific information and research at the Universiti Putra Malaysia.

Currently, the collections deposited in the IR consists of Master and PhD theses, Master and PhD Project Report, Journal Articles, Journal Bulletins, Conference Papers, UPM News, Newspaper Cuttings, Patents and Inaugural Lectures.

As the policy of the university does not permit users to view thesis in full text, access is only given to the first 24 pages only.