Dr. Wenbo Wu, University of Texas at San Antonio presents On Partial Envelope Approach for Modeling Spatial-Temporally Dependent Data

Date: Thursday, February 22, 2024

Start time: 3:00 pm

End time: 4:00 pm

Location: Harris Hall room 4119

Audience: All are welcome to attend

In the new era of big data, modeling multivariate spatial-temporally dependent data is a challenging task due to the dimensionality of the features and complex spatial-temporal associations among the observations across different locations and time points. To improve the estimation efficiency, we propose a spatial-temporal partial envelope model which is parsimonious and effective in modeling high-dimensional spatial-temporal data. The partial envelope model was proposed under a linear coregionalization model framework which allows heterogenous spatial-temporal covariance structure for different components of the response vector. The maximum likelihood estimator for the proposed model can be obtained through a Grassmann manifold optimization. We obtained a complete asymptotic result for the estimator and conduct thorough empirical simulations to demonstrate the soundness and effectiveness of the proposed method. We also apply the proposed model to analyze the crowdsourcing weather data collected from personal weather stations in the United States.

Bio

Dr. Wenbo Wu is the Chair of the Department of Management Science and Statistics, Graham Weston Endowed Professor and an associate professor in management science and statistics at The University of Texas at San Antonio. Before moving to San Antonio, he was an assistant professor at the University of Oregon. Wu received his Ph.D. in statistics from the University of Georgia in 2015.

Sponsor(s): SSOR

Event contact: Dr. Ya Su, suyaf@vcu.edu