| 书目名称 | Restricted Kalman Filtering |
| 副标题 | Theory, Methods, and |
| 编辑 | Adrian Pizzinga |
| 视频video | |
| 概述 | Provides an extensive review of linear state models subject to constraints on the state vector.Contains new proofs for existing results on the subject.Provides new findings useful in understanding sta |
| 丛书名称 | SpringerBriefs in Statistics |
| 图书封面 |  |
| 描述 | In statistics, the Kalman filter is a mathematical method whose purpose is to use a series of measurements observed over time, containing random variations and other inaccuracies, and produce estimates that tend to be closer to the true unknown values than those that would be based on a single measurement alone. This Brief offers developments on Kalman filtering subject to general linear constraints. There are essentially three types of contributions: new proofs for results already established; new results within the subject; and applications in investment analysis and macroeconomics, where the proposed methods are illustrated and evaluated. The Brief has a short chapter on linear state space models and the Kalman filter, aiming to make the book self-contained and to give a quick reference to the reader (notation and terminology). The prerequisites would be a contact with time series analysis in the level of Hamilton (1994) or Brockwell & Davis (2002) and also with linear state models and the Kalman filter – each of these books has a chapter entirely dedicated to the subject. The book is intended for graduate students, researchers and practitioners in statistics (specifi |
| 出版日期 | Book 2012 |
| 关键词 | Econometrics; General linear models; Kalman Filter |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4614-4738-2 |
| isbn_softcover | 978-1-4614-4737-5 |
| isbn_ebook | 978-1-4614-4738-2Series ISSN 2191-544X Series E-ISSN 2191-5458 |
| issn_series | 2191-544X |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Busines |
发表于 2025-3-21 18:57:38
