Lectures

Live Lecture

Just before lecture, about 1:30pm PST on Tues and Thurs, we'll post the webcast link to the lecture. Click on Home (left) to see link.

Week 1

 
General introductory material on types of time series, decomposition, correlation, backshift, differencing, etc.
Microsoft PowerPoint file icon Lec 1 - Introduction to time series2.4M Download
Adobe Acrobat file icon Lec 1 - Introduction to time series1.4M Download View
Microsoft PowerPoint file icon Lec 2 - Covariance & correlation5.4M Download
Adobe Acrobat file icon Lec 2 - Covariance & correlation1.7M Download View

Week 2

 
Stationary & nonstationary model for univariate time series (Tues).
Estimation procedures for fitting time series models (Thurs).
Microsoft PowerPoint file icon Lec 3 - Stationary & nonstationary models5.2M Download
Adobe Acrobat file icon Lec 3 - Stationary & nonstationary models1.1M Download View
Microsoft PowerPoint file icon Lec 4 - Estimation & forecasting.pptx2.8M Download
Adobe Acrobat file icon Lec 4 - Estimation & forecasting.pdf2.4M Download View

Week 3

 
Introduction to univariate state-space models (Tues).
Introduction to multivariate state-space models (Thurs).
Adobe Acrobat file icon Lec 5 - Intro to Univariate State-Spa...pdf862K Download View
R script file icon univariate_example_3.R3K Download
R script file icon univariate_example_1.R3K Download
R script file icon univariate_example_2.R3K Download
R script file icon univariate_example_4.R3K Download
Adobe Acrobat file icon Lec 6 - Intro to multivariate state-s...pdf1.6M Download View I'll work through examples 1 and 2 below during class. Look at the other examples on your own.
R script file icon Lec_6_MARSS_example_1.R2K Download
R script file icon Lec_6_MARSS_example_2.R1K Download
R script file icon Lec_6_MARSS_example_3.R1K Download
R script file icon Lec_6_MARSS_example_4.R1K Download
R script file icon Lec_6_MARSS_example_5.R1K Download

Week 4

 
Including seasonality & covariates in models; missing covariates; colinearity (Tues).
Model selection, multi-model inference (Thurs).
Adobe Acrobat file icon Fitting MARSS models with covariates.pdf253K Download View We'll walk through this lab at the end of Tuesday's lecture.
R script file icon Fitting MARSS models with covariates.R10K Download Just the R code for the lab
Adobe Acrobat file icon Lec 7 - Covariates in MARSS Models.pdf1.2M Download View This is the lecture.
Microsoft PowerPoint file icon Lec 8 - Cross Validation and More For..pptx2.9M Download
Adobe Acrobat file icon Lec 8 - Cross Validation and More For...pdf2.4M Download View

Week 5

 
Uni- & multivariate dynamic linear models (DLMs) (Tues).

Applications of DLMs (Thurs).
Microsoft PowerPoint file icon Lec 9 - Intro to Dynamic Linear Models.pptx5.8M Download
Adobe Acrobat file icon Lec 9 - Intro to Dynamic Linear Models1.1M Download View
Microsoft PowerPoint file icon Lec 10 - Applications of DLMs.pptx23.6M Download
Adobe Acrobat file icon Lec 10 - Applications of DLMs33.2M Download View

Week 6

 
Introduction to the forecast package and exponential smoothing (Tues).
Introduction to dynamic factor analysis (DFA (Thurs).
Unknown file type icon Lec 11 - Exponential Smoothing Models.Rmd13K Download
HTML file icon Lec_11_-_Exponential_Smoothing_Models.html456K Download View source
Adobe Acrobat file icon Lec_11_-_Exponential_Smoothing_Models.pdf335K Download View
Microsoft PowerPoint file icon Lec 12 - Dynamic Factor Analysis.pptx11.9M Download
Adobe Acrobat file icon Lec 12 - Dynamic Factor Analysis.pdf3.0M Download View

Week 7

 
Bayesian estimation in Stan (Tues).
Non-Gaussian models and fitting (Thurs).
Microsoft PowerPoint file icon Lec 13 - Bayesian estimation in Stan.pptx3.6M Download
Adobe Acrobat file icon Lec 13 - Bayesian estimation in Stan.pdf2.3M Download View
Microsoft PowerPoint file icon Lec 14 - Zeros and non-normal data.pptx1.5M Download
Adobe Acrobat file icon Lec 14 - Zeros and non-normal data.pdf1.3M Download View

Week 8

 
Including spatial effects (Tues).
Estimating interactions part I (Thurs).
Microsoft PowerPoint file icon Lec 15 - Including spatial correlation.pptx20.4M Download
Adobe Acrobat file icon Lec 15 - Including spatial correlation.pdf6.5M Download View
R script file icon Lec 15.R7K Download R code for working with some examples shown in lecture
Microsoft PowerPoint file icon Lec 16 - Estimating Interactions I.pptx1.8M Download
Adobe Acrobat file icon Lec 16 - Estimating Interactions I.pdf1.3M Download View
R script file icon Gompertz_example_0.R2K Download
R script file icon Gompertz_example_1.R3K Download
R script file icon Gompertz_example_2.R2K Download
R script file icon Gompertz_example_3.R3K Download
R script file icon Gompertz_example_4.R2K Download
R script file icon GompertzSS_REML.R8K Download
R script file icon LV_example_1.R2K Download
R script file icon LV_example_2.R1K Download
R script file icon LV_example_3.R9K Download
R script file icon LV_example_4.R10K Download

Week 9

 
Estimating interactions; continued (Tues).
Estimating intervention effects (Thurs).
Microsoft PowerPoint file icon Lec 17 - Estimating Interactions II.pptx8.6M Download
Adobe Acrobat file icon Lec 17 - Estimating Interactions II.pdf2.4M Download View
Microsoft PowerPoint file icon Lec 18 - Analyses of intervention eff..pptx16.9M Download
Adobe Acrobat file icon Lec 18 - Analyses of intervention eff...pdf7.7M Download View

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