Closed-form expression for finite predictor coefficients of multivariate ARMA processes
Finite predictor coefficients
Multivariate ARMA processes
We derive a closed-form expression for the finite predictor coefficients of multivariate ARMA (autoregressive moving-average) processes. The expression is given in terms of several explicit matrices that are of fixed sizes independent of the number of observations. The significance of the expression is that it provides us with a linear-time algorithm to compute the finite predictor coefficients. In the proof of the expression, a correspondence result between two relevant matrix-valued outer functions plays a key role. We apply the expression to determine the asymptotic behavior of a sum that appears in the autoregressive model fitting and the autoregressive sieve bootstrap. The results are new even for univariate ARMA processes.
The author was supported by the JSPS Grant-in-Aid 17K05302 (Inoue, A., Hiroshima Univ.).
Journal of Multivariate Analysis
|date of issued||
© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
This is not the published version. Please cite only the published version. この論文は出版社版ではありません。引用の際には出版社版をご確認、ご利用ください。
Graduate School of Advanced Science and Engineering
The full-text file will be made open to the public on 1 April 2022 in accordance with publisher's 'Terms and Conditions for Self-Archiving'