报告人：Jingru Mu (Kansas State University)
时间：2022年11月15日星期二9:30-10:30
腾讯会议：274 226 015
摘要：
In this talk, the speaker will present a new volatility model by allowing spatially varying coefficients in spatial generalized autoregressive conditional heteroskedasticity (SGARCH) models. This model captures volatility behaviors over space and investigates the relationship between some explanatory variables and the volatility at each location. A two-stage quasi-likelihood maximization via BPST is developed to estimate the model over a complicated domain. The speaker will also present the theoretical properties of the proposed estimators. We conduct both simulation studies and real-data applications to demonstrate the performance of our approach.
报告人简介：
Dr. Jingru Mu has joined the Department of Statistics at Kansas State University as an Assistant Professor since August 2019. Her current responsibilities include teaching mathematical statistics and researching complex and large-scale data analysis, and non/semi-parametric spatio-temporal models in environmental science, natural resources, and economics. She participated in projects on flexible spatial models and developing methodologies. She received her Ph.D. in statistics from Iowa State University in 2019 and an M.S in statistics from the University of California, Davis in 2015.
邀请人：张园园