Embedding a Gaussian discrete-time autoregressive moving average process in a Gaussian continuous-time autoregressive moving average process

被引:9
作者
Huzii, Mituaki [1 ]
机构
[1] Chuo Univ, Hachioji, Tokyo, Japan
关键词
embedding; discrete-time ARMA; continuous-time ARMA; autocovariance; spectral density; sampled process;
D O I
10.1111/j.1467-9892.2006.00520.x
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Embedding a discrete-time autoregressive moving average (DARMA) process in a continuous-time ARMA (CARMA) process has been discussed by many authors. These authors have considered the relationship between the autocovariance structures of continuous-time and related discrete-time processes. In this article, we treat the problem from a slightly different point of view. We define embedding in a more rigid way by taking account of the probability structure. We consider Gaussian processes. First we summarize the necessary and sufficient condition for a DARMA process to be able to be embedded in a CARMA process. Secondly, we show a concrete condition such that a DARMA process can be embeddable in a CARMA process. This condition is new and general. Thirdly, we show some special cases including new examples. We show how we can examine embeddability for these special cases.
引用
收藏
页码:498 / 520
页数:23
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