دورية أكاديمية
Recursive Least Squares Estimator with Multiple Exponential Windows in Vector Autoregression
| العنوان: | Recursive Least Squares Estimator with Multiple Exponential Windows in Vector Autoregression |
|---|---|
| المؤلفون: | An Hongzhi, Li Zhiguo |
| المساهمون: | Institute of Applied Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Department of Biomathematics, Peking University Health Science Center |
| المصدر: | CSCD |
| بيانات النشر: | Acta Mathematicae Applicatae Sinica |
| سنة النشر: | 2002 |
| المجموعة: | Peking University Institutional Repository (PKU IR) / 北京大学机构知识库 |
| مصطلحات موضوعية: | exponential window, rectangular window, multiple exponential window, weighted least squares method, vector autoregression |
| الوصف: | In the parameter tracking of time-varying systems, the ordinary method is weighted least squares with the rectangular window or the exponential window. In this paper we propose a new kind of sliding window called the multiple exponential window, and then use it to fit time-varying Gaussian vector autoregressive models. The asymptotic bias and covariance of the estimator of the parameter for time-invariant models are also derived. Simulation results show that the multiple exponential windows have better parameter tracking effect than rectangular windows and exponential ones. ; 中国科学引文数据库(CSCD) ; 1 ; 85-102 ; 18 |
| نوع الوثيقة: | journal/newspaper |
| اللغة: | English |
| العلاقة: | Acta Mathematicae Applicatae Sinica.2002,18(1),85-102.; 1358458; http://hdl.handle.net/20.500.11897/427365Test |
| الإتاحة: | https://doi.org/20.500.11897/427365Test https://hdl.handle.net/20.500.11897/427365Test |
| رقم الانضمام: | edsbas.2F10C662 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |