STA572: Time Series Analysis and Forecasting
Course Notes — Universiti Teknologi MARA
Welcome to the course notes for STA572/570: Time Series Analysis and Forecasting.
Instructor
Muhammad Asmu’i Bin Abdul Rahim Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA
Course Data
All datasets used in this course are available at: GitHub — Course Data
Chapters
| Chapter | Topic |
|---|---|
| Chapter 1 | Introduction to Time Series |
| Chapter 2 | Univariate Modelling Techniques |
| Chapter 3 | Econometric Modelling |
| Chapter 4 | Stochastic Processes |
| Chapter 5 | Box-Jenkins Methodology |
Software
All analysis in this course is performed in R. Install all required packages with:
install.packages(c(
# Core time series
"forecast", "fpp2", "TSA", "tseries",
# Tidyverse-style time series (Chapter 5)
"fable", "feasts", "tsibble",
# Data manipulation
"dplyr", "lubridate",
# Visualisation
"ggplot2", "ggpubr", "gridExtra",
# Regression diagnostics (Chapter 3)
"lmtest", "car",
# Table formatting (Chapter 1)
"kableExtra",
# Live market data (Chapter 5)
"quantmod"
))| Package | Used in | Purpose |
|---|---|---|
forecast, fpp2 |
C1–C5 | Forecasting models and plots |
TSA |
C1 | Intervention analysis |
tseries |
C4, C5 | ADF unit-root test |
fable, feasts, tsibble |
C5 | Tidyverse time series modelling |
dplyr |
C5 | Data wrangling |
lubridate |
C1 | Date/time handling |
ggplot2, ggpubr, gridExtra |
C1–C5 | Graphics |
lmtest, car |
C3 | Regression diagnostics |
kableExtra |
C1 | Formatted tables |
quantmod |
C5 | Download S&P 500 data from Yahoo Finance |
Note
Source code for all chapters is available on GitHub: github.com/asmuie-analytics