頁籤選單縮合
| 題 名 | Asymptotic Inference for Spatial CDFs over Time |
|---|---|
| 作 者 | Zhu,Jun; Lahiri,S. N.; Cressie,Noel; | 書刊名 | Statistica Sinica |
| 卷 期 | 12:3 2002.07[民91.07] |
| 頁 次 | 頁843-861 |
| 分類號 | 319.5 |
| 關鍵詞 | Environmental resource assessment and monitoring; Functional central limit theorem; Spatial cumulative distribution function; Spatial prediction; Spatial subsampling; Spatio-temporal process; |
| 語 文 | 英文(English) |
| 英文摘要 | A spatial cumulative distribution function (SCDF) is a random function that provides a statistical summary of a random process over a spatial domain of interest. In this paper, we consider a spatio-temporal process and establish statistical methodology to analyze changes in the SCDF over time. We develop hypothesis testing to detect a difference in the spatial random processes at two time points, and we construct a prediction interval to quantify such discrepancy in the corresponding SCDFs. Using a spatial subsampling method, we show that our inferences are valid asymptotically. As an illustration, we apply these inference procedures to test and predict changes in the SCDF of an ecological index for foliage condition of red maple trees in the state of Maine in the early 1990s. |
本系統中英文摘要資訊取自各篇刊載內容。