A nonparametric assessment of properties of space-time covariance functions

• 成果类型: Article
• 署名作者: Li, Bo; Genton, Marc G.; Sherman, Michael
• 署名单位: National Center Atmospheric Research (NCAR) - USA; University of Geneva; Texas A&M University System; Texas A&M University College Station
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/016214507000000202
• 发表日期: 2007
• 页码: 736-744
• 关键词: Separability; variance; models

摘要

We propose a unified framework for testing various assumptions commonly made for covariance functions of stationary spatio-temporal random fields. The methodology is based on the asymptotic normality of space-time covariance estimators. We focus on tests for full symmetry and separability in this article, but our framework naturally covers testing for isotropy and Taylor's hypothesis. Our test successfully detects the asymmetric and nonseparable features in two sets of wind speed data. We per-form simulation experiments to evaluate our test and conclude that our method is reliable and powerful for assessing common assumptions on space-time covariance functions.