Main Article Content

Abstract

The autocorrelation function (ACF) measures the correlation between observations at different   distances apart. We derive explicit equations for generalized heteroskedasticity ACF for moving average of order q, MA(q). We consider two cases: Firstly: when the disturbance term follow the general covariance matrix structure Cov(wi, wj)=S with si,j¹ 0 " i¹j . Secondly: when the diagonal elements of S are not all identical but sij = 0 " i¹j, i.e. S=diag(s11, s22,…,stt). The forms of the explicit equations depend essentially on the moving average coefficients and covariance structure of the disturbance terms.

 

Keywords

Heteroscedasticity Homoscedasticity Autocorrelation Moving Average Covariance.

Article Details

Author Biography

Samir Khaled Safi, The Islamic University of Gaza Gaza - Palestine

My research interests are in Time Series Analysis and Forecasting, Regression and Multivariate Statistics.

How to Cite
Safi, S. K. (2014). Generalized Heteroskedasticity ACF for Moving Average Models in Explicit Forms. Pakistan Journal of Statistics and Operation Research, 9(4), 381-393. https://doi.org/10.18187/pjsor.v9i4.644