CSE 683 : Time Series Analysis and Forecasting
 

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Lectures
  

Lecture

Contents & Refs

 

Week 1

- Introduction to Forecasting
    - Ch 1 Slide (PDF)
Week 2-3
- Choosing R or Python for data analysis?  (HTM)
- R (programming language) (
HTM)
- R Project (HTM)
- CRAN (HTM)
- R IDEs  (HTM)
    - RStudio (HTM)
    - Revolution R (HTM)
- R Documentation (HTM)

- Using RStudio (PDF)

- Using R
    - R Tutorial from tutorialspoint.com (PDF) (HTM)
    - R for Beginners  (PDF)
    - R Programming for Data Science by Roger D. Peng (PDF)
    - Try R Code School (
HTM)
    - R tutorial (cyclismo.org) (
HTM) 
    - Introduction to R (
HTM) 
    - R Tutorials (HTM)
    - R Manulas (HTM)
   

    - R Cheat Sheets (HTM1, HTM2)
    - R Reference Card (
PDF)
    - Statistical Computing (HTM)
Week 4 - R for Data Science (HTM)
- Data Transformation in R (PDF)
- Data Wrangling in the Tidyverse (PDF)

- https://www.datacamp.com/courses/introduction-to-the-tidyverse
- https://www.tidyverse.org/learn/
Week 5  The forecaster's toolbox
    - Ch2 Slide (PDF)

    - fpp Ch2 (HTM)

    - fpp2 Ch2 (HTM), Ch3 (HTM)
Week 6 - Judgemental Forecasts
    - fpp2 Ch4 (HTM), fpp Ch3  (HTM

Week 7 - Linear regression models  
   - Ch5 Simple Regression (PDF), - Ch5 Multiple Regression (PDF)


   - fpp2 Ch5 (HTM),
     fpp Ch4 (
HTM), fpp Ch5 (HTM)


   - Prediction (PPT)
Week 8 - Time Series Decompositon
    - Ch6 Slide (PDF)

    - fpp Ch6 (HTM)

    - fpp2 Ch6 (HTM)
Week 9 - Exponential Smoothing
 
   - Ch7 Slide1 (PDF)
   - Ch7 Slide2 (PDF)

   - fpp Ch7 (HTM)

   - fpp2 Ch7 (HTM)

   - Test Bank Answers (PDF)

   - Take-home (PDF)
Week 10 Vize
Week 11 - ARIMA Models

   - Diffrencing (PDF)
   - Nonseasonal ARIMA (PDF)
   - Seasonal ARIMA (PDF)

   - fpp Ch 8 (HTM)

   - fpp2 Ch 8 (HTM)
Week 12 - Advanced forecasting methods
   - fpp Ch 9 (HTM)
Week 13  
Week 14  
  
Presentations
 
HomeWorks
Projects
 
Class Resources

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