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Statistical Methods for Spatio-temporal Data

Thursday, June 10, 2021

11:00 am - 12:00 pm

About the Event

“Spatio-temporal statistics” concern statistical methods for data measured in space and time. Many datasets we encounter are spatio-temporal data in the sense that observations are collected from multiple spatial locations over time (e.g. trend of housing price in a city, daily maximum temperature measured from multiple weather stations over time). Data from many scientific areas, including atmospheric science, geography, business, social science and epidemiology commonly require spatio-temporal statistical methods for accurate description of the data as well as prediction. This talk will give a general overview of spatio-temporal statistics with several real data application examples.

About the Speaker

Mikyoung Jun is the ConocoPhillips Data Science Professor in the Department of Mathematics. Prior to joining UH, Jun was a professor in the Department of Statistics at Texas A&M University. Her research is highly multidisciplinary, and she is currently collaborating with atmospheric and climate scientists and political scientists at Texas A&M University, as well as geophysicists at UH.



Martin Huarte Espinosa
Associate Director
HPE Data Science Institute