| DC Field | Value | Language |
|---|
| dc.contributor.author | Shibalko, S. | - |
| dc.contributor.author | Kharin, Y. | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2024-02-23T08:35:23Z | - |
| dc.date.available | 2024-02-23T08:35:23Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.citation | Shibalko, S. Parsimonious models of multivariate binary time series: statistical estimation and forecasting / S. Shibalko, Y. Kharin // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 296–299. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/54352 | - |
| dc.description.abstract | This paper is devoted to parsimonious models of multivariate binary time series. Consistent asymptotically
normal statistical estimators for the parameters of proposed parsimonious models are constructed. Algorithms for statistical estimation of model parameters and forecasting of future states of time series are presented. Results of computer experiments on simulated and real statistical discrete-valued data are given. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | BSU | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | binary time series | en_US |
| dc.subject | multivariate data | en_US |
| dc.subject | statistical estimation | en_US |
| dc.subject | parsimonious models | en_US |
| dc.subject | statistical forecasting | en_US |
| dc.title | Parsimonious models of multivariate binary time series: statistical estimation and forecasting | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)
|
