期刊名称：Pakistan Journal of Statistics and Operation Research
印刷版ISSN：2220-5810
出版年度：2013
卷号：9
期号：4
页码：381-393
DOI：10.1234/pjsor.v9i4.644
语种：English
出版社：College of Statistical and Actuarial Sciences
摘要：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,j ¹ 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.
关键词：Statistics, Time Series, Autocorrelation function;Heteroscedasticity, Homoscedasticity, Autocorrelation, Moving Average, Covariance.;62
