Skip to main content
Extreme Statistics
XSTAT
Extreme Statistics
Main navigation
Home
People
Principal Investigators
Postdoctoral Fellows
Students
All Profiles
Alumni
Former Members
Events
All Events
Events Calendar
News
Pages
Publications
ISL Publications Repository
Research Output
About
Contact Us
Publications
Teaching
geospatial statistics
Spatial Models and Extreme-Value Methods for Wildfire Risk Assessment
Daniela Cisneros, Ph.D. Student, Statistics
Sep 11, 16:00
-
17:00
B3 L5 R5220
extreme statistics
Applied Machine Learning
geospatial statistics
The statistical modeling of spatial and extreme events provides a framework for the development of techniques and models to describe natural phenomena in a variety of environmental, geoscience, and climate science applications. In a changing climate, various natural hazards, such as wildfires, are believed to have evolved in frequency, size, and spatial extent, although regional responses may vary.