Volume no :2, Issue no: 1, September (2009)

Journal of Statistics: Advances in Theory and Applications

TIME SERIES PROPERTIES OF THE CLASS OF FIRST ORDER AUTOREGRESSIVE PROCESSES WITH GENERALIZED MOVING AVERAGE ERRORS

Author's: Thulasyammal Ramiah Pillai, Mahendran Shitan and Shelton Peiris
Pages: [71] - [92]
Received Date: August 28, 2009
Submitted by:

Abstract

A new class of time series models known as Generalized Autoregressive of order one with first order moving average errors has been introduced in order to reveal some 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 these new results reduce to the standard ARMA results and therefore, applicable in many special cases. Numerical values of the ACF are obtained and compared with ARMA results.

Keywords

autoregression, moving average, errors, autocorrelations, variance, autocovariance, spectral density, estimation, time series, fractional differencing, long memory.