学术报告
New Classes of Multivariate Covariance Functions-Tatiyana Apanasovich (George Washington University)
题目： New Classes of Multivariate Covariance Functions
报告人： Tatiyana Apanasovich (George Washington University)
Abstract
The class which is refereed to as the Cauchy family allows for the simultaneous modeling of the long memory dependence and correlation at short and intermediate lags. We introduce a valid parametric family of cross-covariance functions for multivariate spatial random fields where each component has a covariance function from a Cauchy family. We present the conditions on the parameter space that result in valid models with varying degrees of complexity. We discuss practical implementations, including reparameterizations to reflect the conditions on the parameter space. We show results of various Monte Carlo simulation experiments to explore the performances of our approach in terms of estimation and cokriging. The application of the proposed multivariate Cauchy model is illustrated on a dataset from the field of Satellite Oceanography.
时间： 5月11日（周四）下午4:00-5:00
地点：首都师范大学本部教二楼924教室
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