Academic Journal
On Optimal Adaptive Prediction of Multivariate Autoregression
| Title: | On Optimal Adaptive Prediction of Multivariate Autoregression |
|---|---|
| Authors: | Kusainov, Marat I., Vasiliev, Vyacheslav A. |
| Contributors: | Томский государственный университет Факультет прикладной математики и кибернетики Кафедра высшей математики и математического моделирования, Томский государственный университет Факультет прикладной математики и кибернетики Публикации студентов и аспирантов ФПМК |
| Source: | Sequential Analysis. 2015. Vol. 34, № 2. P. 211-234 |
| Publisher Information: | Informa UK Limited, 2015. |
| Publication Year: | 2015 |
| Subject Terms: | размер выборки, авторегрессия, адаптивные предикторы, асимптотическая эффективность рисков, 0101 mathematics, 16. Peace & justice, 01 natural sciences |
| Description: | The problem of asymptotic efficiency of adaptive one-step predictors for a stable multivariate first-order autoregressive process (AR(1)) with unknown parameters is considered. The predictors are based on the truncated estimators of the dynamic matrix parameter. The truncated estimation method is a modification of the truncated sequential estimation method that makes it possible to obtain estimators of ratio-type functionals with a given accuracy by samples of fixed size. The criterion of optimality is based on the loss function, defined as a sum of sample size and squared prediction error's sample mean. The cases of known and unknown variance of the noise model are studied. In the latter case the optimal sample size is a special stopping time. The simulation results are given. |
| Document Type: | Article |
| File Description: | application/pdf |
| Language: | English |
| ISSN: | 1532-4176 0747-4946 |
| DOI: | 10.1080/07474946.2015.1030977 |
| Access URL: | http://www.tandfonline.com/doi/citedby/10.1080/07474946.2015.1030977 http://vital.lib.tsu.ru/vital/access/manager/Repository/vtls:000513552 |
| Accession Number: | edsair.doi.dedup.....a1e5f6c04f36b0951e6e76dbab6a63d2 |
| Database: | OpenAIRE |
| ISSN: | 15324176 07474946 |
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| DOI: | 10.1080/07474946.2015.1030977 |