Continuous-time autoregressive moving average processes in discrete time: representation and embeddability

被引：8

作者：

Thornton, Michael A. ^{[1
]}

Chambers, Marcus J. ^{[2
]}

机构：

[1] Univ York, Heslington YO10 5DD, N Yorkshire, England

[2] Univ Essex, Colchester CO4 3SQ, Essex, England

来源：

JOURNAL OF TIME SERIES ANALYSIS | 2013年 / 34卷 / 05期

基金：

英国经济与社会研究理事会;

关键词：

Continuous time; ARMA process; discrete-time representation; embedding; GAUSSIAN ESTIMATION; DYNAMIC-MODELS; STOCHASTIC TRENDS; ARMA PROCESSES; STATIONARY; PARAMETERS; SYSTEMS;

D O I：

10.1111/jtsa.12030

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This article explores techniques to derive the exact discrete-time representation for data generated by a continuous-time autoregressive moving average (ARMA) process, augmenting existing methods with a stochastic integration-by-parts formula. The continuous-time ARMA(2, 1) system is considered in detail, and a mapping from the parameters of a univariate discrete-time ARMA(2, 1) process to a univariate continuous-time ARMA(2, 1) process observed at discrete intervals is derived. This is used to derive conditions for the embeddability of such processes.

引用

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页码：552 / 561

页数：10

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