A note on time-reversibility of multivariate linear processes

被引:21
|
作者
Chan, KS [1 ]
Ho, LH
Tong, H
机构
[1] Univ Iowa, Dept Stat & Actuarial Sci, Iowa City, IA 52242 USA
[2] Wichita State Univ, Dept Math & Stat, Wichita, KS 67260 USA
[3] London Sch Econ, Dept Stat, London WC2A 2AE, England
关键词
cumulant; distributional equivalence; non-Gaussian distribution; T-distribution; time series; symmetry;
D O I
10.1093/biomet/93.1.221
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
We derive some readily verifiable necessary and sufficient conditions for a multivariate non-Gaussian linear process to be time-reversible, under two sets of conditions on the contemporaneous dependence structure of the innovations. One set of conditions concerns the case of independent-component innovations, in which case a multivariate non-Gaussian linear process is time-reversible if and only if the coefficients consist of essentially asymmetric columns with column-specific origins of symmetry or symmetric pairs of columns with pair-specific origins of symmetry. On the other hand, for dependent-component innovations plus other regularity conditions, a multivariate non-Gaussian linear process is time-reversible if and only if the coefficients are essentially symmetric about some origin.
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页码:221 / 227
页数:7
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