Modeling and Inference of Local Stationarity

主讲人: Tailen Hsing

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

主持人: Wei Zhong

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
期数: 厦门大学高级计量经济学与统计学系列讲座2018春季学期第二讲(总第103讲)
主办单位: SOE&WISE
承办单位: 统计系
类型: 系列讲座

How to apply

We invite you to explore our various study programs. By joining us, we are sure you would find your time here intellectually rewarding and challenging.


Contact information

Tel.: +86(0)592-2189805
Address: N106 Economics Building, Xiamen University, Xiamen, Fujian, P.R. China 361005

WeChat subscription account QR code