Asymptotic distributions of the sample mean, autocovariances, and autocorrelations of long-memory time series

被引:104
作者
Hosking, JRM
机构
[1] IBM Research Division, T.J. Watson Research Center, Yorktown Heights
关键词
central limit theorem; fractional ARIMA process; fractional differencing; noncentral limit theorem; Rosenblatt distribution;
D O I
10.1016/0304-4076(95)01740-2
中图分类号
F [经济];
学科分类号
02 ;
摘要
We derive the asymptotic distributions of the sample mean, autocovariances, and autocorrelations for a time series whose autocovariance function {gamma(k)} has the powerlaw decay gamma(k) similar to gamma k(-alpha), lambda > 0, 0 < alpha < 1, as k --> infinity. The results differ in important respects From the corresponding results for short-memory processes, whose autocovariance functions are absolutely summable. For long-memory processes the variances of the sample mean, and of the sample autocovariances and autocorrelations for 0 < alpha less than or equal to 1/2, are not of asymptotic order n(-1). When 0 < alpha < 1/2 the asymptotic distributions of the sample autocovariances and autocorrelations are not Normal.
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页码:261 / 284
页数:24
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