Short Course: "Spatial Linear Models for Environmental Data"
Presented by Jay Ver Hoef, Dale Zimmerman, and Michael Dumelle
This full day (8:30 am - 5:00 pm) short course will be based on the book of the same name:
https://www.routledge.com/Spatial-Linear-Models-for-Environmental-Data/Zimmerman-Ver-
Hoef/p/book/9780367183349
Outline:
1. Introduction to spatial data, software, ESDA [Intro through Chapter 3 of the book]
2. OLS and GLS estimation, including spatial confounding [Chapters 4-5]
3. Various geostatistical and spatial weights models and variations such as anisotropy
[Chapters 6-7]
4. Likelihood-based estimation, including generalized linear mixed models [Chapter 8,
Section 12.6]
5. Spatial prediction (including block kriging, conditional simulation, etc.) [Chapter 9]
6. Sampling and spatial design-of-experiments [Chapters 10, 11]
Additional details and links to software and data to come!
Session #1 -
- Robert Lund, UC Santa Cruz
- Sudipto Banerjee, UCLA
- Veronica Berrocal, UC Irvine
- Matthias Katzfuss, University of Wisconsin-Madison
Session #2 -
- Yawen Guan, Colorado State University
- Trevor Harris, Texas A&M University
- Likun Zhang, University of Missouri
- Lyndsay Shand, Sandia National Laboratories
Session #3 -
- Will Kleiber, University of Colorado Boulder
- Richard Smith, University of North Carolina
- Barb Bailey, San Diego State University
Session #4 -
- Bo Li, University of Illinois
- Matt Heaton, Brigham Young University
- Dan Cooley, Colorado State University
Session #5 -
- Doug Nychka, Colorado School of Mines
- Andy Finley, Michigan State University
- Joe Guinness, Cornell University