University of Illinois Urbana-Champaign

Spatio-temporal data modeling with applications to weather and disease

Sass, Danielle

Content Files
SASS-DISSERTATION-2021.pdf

Permalink

https://hdl.handle.net/2142/110813

Description

Title
Spatio-temporal data modeling with applications to weather and disease
Author(s)
Sass, Danielle
Issue Date
2021-04-16
Director of Research (if dissertation) or Advisor (if thesis)
Li, Bo
Doctoral Committee Chair(s)
Li, Bo
Committee Member(s)
  • Simpson, Douglas
  • Douglas, Jeffrey
  • Park, Trevor
Department of Study
Statistics
Discipline
Statistics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2021-09-17T04:04:25Z
Keyword(s)
  • adulticide spray
  • fused penalties
  • HIV prediction
  • spatial extremes
  • West Nile virus
Abstract
Meteorological and epidemiological data are oftentimes collected over many years at various locations. In such cases, it is beneficial to use spatio-temporal modeling to account for trends and the correlation of nearby observations. This thesis explores applications to spatio-temporal modeling. First, a method is developed to model the marginal distribution of spatial extreme values at a large scale quickly while allowing flexibility by introducing a fused penalty for parameter regularization. Next, various models are considered and evaluated to compare county-level HIV prediction over the US to determine if spatial models are advantageous when an abundance of covariates are available that capture the data variability. Lastly, a generalized additive model with spatial and temporal covariates is utilized to evaluate the impact of adulticide spraying on gravid Culex mosquitoes in the North Shore Mosquito Abatement District of Illinois.
Graduation Semester
2021-05
Type of Resource
Thesis
Permalink
http://hdl.handle.net/2142/110813
Copyright and License Information
Copyright 2021 Danielle Sass

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