A note on the covariance structure of a continuous-time ARMA process

被引:0
|
作者
Tsai, HS [1 ]
Chan, KS
机构
[1] Tunghai Univ, Dept Stat, Taichung 407, Taiwan
[2] Univ Iowa, Dept Stat & Actuarial Sci, Iowa City, IA 52242 USA
关键词
irregularly sampled data; Kalman filter; stochastic differential equations;
D O I
暂无
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We have derived some matrix equations for speedy computation of the conditional covariance kernel of a discrete-time process obtained from irregularly sampling an underlying continuous-time ARMA process. These results are applicable to both stationary and non-stationary ARMA processes. We have also demonstrated that these matrix results can be useful in shedding new insights on the covariance structure of a continuous-time ARMA process.
引用
收藏
页码:989 / 998
页数:10
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