Applied Spatio-temporal Statistics
Preface
1
Day 1 (January 18)
1.1
Course pre-assessment
1.2
Welcome
1.3
Course format
1.4
Reading
1.5
Opening example: Human movement
2
Day 2 (January 25)
2.1
Announcements
2.2
Opening example: Human movement
3
Day 3 (January 30)
3.1
Announcements
3.2
Statistical models
3.3
Matrix review
3.4
Distribution theory review
3.5
Mathematical model review
3.6
Summary and comments
4
Day 4 (February 1)
4.1
Announcements
4.2
Statistical models
4.3
Matrix review
4.4
Distribution theory review
5
Day 5 (February 6)
5.1
Announcements
5.2
Distribution theory review
5.3
Mathematical model review
6
Day 6 (February 8)
6.1
Announcements
6.2
Mathematical model review
6.3
Summary and comments
6.3.1
Motivating data example
6.4
Hierarchical models
7
Day 7 (February 13)
7.1
Announcements
7.2
Motivating data example
7.3
Hierarchical models
7.3.1
The data model
7.3.2
The process model
7.3.3
The parameter model
8
Day 8 (February 15)
8.1
Announcements
8.2
Motivating data example
8.3
Simulating data from the prior predictive distribution
8.4
Model fitting
8.5
Inference and predictions
9
Day 9 (February 20)
9.1
Announcements
9.2
Review
9.3
Extreme precipitation in Kansas
10
Day 10 (February 22)
10.1
Announcements
10.2
Extreme precipitation in Kansas
10.3
Intro to GIS
10.3.1
Shapefiles
10.3.2
Raster
10.3.3
Points
10.3.4
Summary
11
Day 11 (February 27)
11.1
Announcements
11.2
Extreme precipitation in Kansas
11.3
Gaussian process
11.3.1
Multivariate normal distribution
11.4
Linear models for correlated errors
11.5
Extreme precipitation in Kansas
12
Day 12 (February 29)
12.1
Announcements
12.2
Extreme precipitation in Kansas
12.3
Linear models for correlated errors
12.4
Hierarchical models
12.5
Extreme precipitation in Kansas
13
Day 13 (February March 5)
13.1
Announcements
14
Day 14 (February March 7)
14.1
Announcements
15
Day 15 (March 19)
15.1
Announcements
15.2
Review
15.3
Extreme precipitation in Kansas
16
Day 16 (March 21)
16.1
Announcements
17
Day 17 (March 26)
17.1
Announcements
17.2
Spatio-temporal models for disease data
18
Day 18 (March 28)
18.1
Announcements
19
Day 19 (April 2)
19.1
Announcements
19.2
Spatio-temporal models for disease data
20
Day 20 (April 4)
20.1
Announcements
21
Day 21 (April 9)
21.1
Announcements
21.2
Spatio-temporal models for disease data
22
Day 22 (April 11)
22.1
Announcements
23
Day 23 (April 16)
23.1
Announcements
23.2
Spatio-temporal models for disease data
23.3
Earthquake data
23.4
Spatio-temporal models for earthquake data
24
Day 24 (April 18)
24.1
Announcements
25
Day 25 (April 23)
25.1
Announcements
25.2
Earthquake data
25.3
Spatio-temporal models for earthquake data
26
Day 26 (April 26)
26.1
Announcements
27
Day 27 (April 30)
27.1
Announcements
27.2
Spatio-temporal models for earthquake data
27.3
Mechanistic spatio-temporal models
28
Day 28 (May 2)
28.1
Announcements
29
Activity 1
30
Activity 2
31
Activity 3
31.1
Motivation
31.2
Data
31.3
Goal
31.4
Prompts
32
Portfolio Assignment
32.1
Grading
33
Final project
33.1
Assignment
33.2
Things to consider
33.3
Grading Rubric
33.4
Examples of A quality work from a similar class
34
Peer review
Published with bookdown
Applied Spatio-temporal Statistics
26
Day 26 (April 26)
26.1
Announcements
In-class workday!
Please come prepared to work on Activity 3 and final project