Publication in refereed journal
香港中文大学研究人员 ( 现职)
| 黄镇山教授 (金融学系) |
全文
| 数位物件识别号 (DOI) http://dx.doi.org/10.1002/cjs.5550350112 |
引用次数
Web of Sciencehttp://aims.cuhk.edu.hk/converis/portal/Publication/18WOS source URL
其它资讯
摘要The authors show how to extend univariate mixture autoregressive models to a multivariate time series context. Similar to the univariate case, the multivariate model consists of a mixture of stationary or nonstationary autoregressive components. The authors give the first and second order stationarity conditions for a multivariate case up to order 2. They also derive the second order stationarity condition for the univariate mixture model up to arbitrary order. They describe an EM algorithm for estimation, as well as a diagnostic checking procedure. They study the performance of their method via simulations and include a real application.
着者Fong PW, Li WK, Yau CW, Wong CS
期刊名称Canadian Journal of Statistics
出版年份2007
月份3
日期1
卷号35
期次1
出版社CANADIAN JOURNAL STATISTICS
页次135 - 150
国际标準期刊号0319-5724
电子国际标準期刊号1708-945X
语言英式英语
关键词diagnostic checking; EM algorithm; mixture vector autoregressive model; multivariate time series; stationarity
Web of Science 学科类别Mathematics; Statistics & Probability; STATISTICS & PROBABILITY
