Closed-form expression for finite predictor coefficients of multivariate ARMA processes
Journal of Multivariate Analysis 176 巻
104578- 頁
2020-03 発行
アクセス数 : 277 件
ダウンロード数 : 45 件
今月のアクセス数 : 3 件
今月のダウンロード数 : 2 件
この文献の参照には次のURLをご利用ください : https://ir.lib.hiroshima-u.ac.jp/00050477
ファイル情報(添付) |
JourMultiAna_176_104578.pdf
154 KB
種類 :
全文
エンバーゴ :
2022-04-01
|
タイトル ( eng ) |
Closed-form expression for finite predictor coefficients of multivariate ARMA processes
|
作成者 | |
収録物名 |
Journal of Multivariate Analysis
|
巻 | 176 |
開始ページ | 104578 |
抄録 |
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.
|
著者キーワード |
Finite predictor coefficients
Multivariate ARMA processes
Closed-form expression
Linear-time algorithm
|
内容記述 |
The author was supported by the JSPS Grant-in-Aid 17K05302 (Inoue, A., Hiroshima Univ.).
|
言語 |
英語
|
資源タイプ | 学術雑誌論文 |
出版者 |
Elsevier
|
発行日 | 2020-03 |
権利情報 |
© 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。
|
出版タイプ | Author’s Original(十分な品質であるとして、著者から正式な査読に提出される版) |
アクセス権 | オープンアクセス |
収録物識別子 |
[ISSN] 0047-259X
[DOI] 10.1016/j.jmva.2019.104578
[DOI] https://doi.org/10.1016/j.jmva.2019.104578
|
備考 | 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' |