頁籤選單縮合
| 題 名 | Comments on Pairwise Likelihood in Time Series Models |
|---|---|
| 作 者 | Davis, Richard A.; Yau, Chun Yip; | 書刊名 | Statistica Sinica |
| 卷 期 | 21:1 2011.01[民100.01] |
| 頁 次 | 頁255-277 |
| 分類號 | 319.711 |
| 關鍵詞 | ARFIMA model; Composite likelihood; Linear time series; Pairwise likelihood; Poisson autoregressive model; |
| 語 文 | 英文(English) |
| 英文摘要 | This note is concerned with the asymptotic properties of pairwise likelihood estimation procedures for linear time series models. The latter includes ARMA as well as fractionally integrated ARMA processes, where the fractional integration parameter . In some cases, including AR(1) processes and long-memory processes with , the loss in efficiency in using pairwise likelihood methods is slight. On the other hand, for some models such as the MA(1), the loss in efficiency can be large, and for long-memory models with , the pairwise likelihood estimator is not even asymptotically normal. A comparison between using all pairs and consecutive pairs of observations in defining the likelihood is given. We also explore the application of pairwise likelihood to a popular nonlinear model for time series of counts. In this case, the likelihood based on the entire data set cannot be computed without resorting to simulation-based procedures. On the other hand, it is possible to numerically compute the pairwise likelihood precisely. We illustrate the good performance of pairwise likelihood in this case. |
本系統中英文摘要資訊取自各篇刊載內容。