Modeling and Inference of Local Stationarity

主讲人: Tailen Hsing

CV: Upload/File/2018/4/20180416041956576.pdf

主持人: Muyi Li

Abstract: Stationarity is a common assumption in spatial statistics. The justification is often that stationarity is a reasonable approximation to the true state of dependence if we focus on spatial data "locally." In this talk, we first review various known approaches for modeling nonstationary spatial data. We then examine a particular notion of local stationarity in more detail. To illustrate, we will focus on the multi-fractional Brownian motion, for which a thorough analysis could be conducted assuming data are observed on a regular grid. Finally, extensions to more general settings that relate to Matheron's intrinsic random functions will be briefly discussed. 

时间: 2018-04-27(Friday)16:40-18:00
地点: D236, Econ Building
主办单位: SOE&WISE
承办单位: 统计系
类型: 系列讲座