etc3550_intro.qmd

---
title: "ETC3550/ETC5550 Applied forecasting"
pdf-engine: pdflatex
fig-width: 7.5
fig-height: 3.5
format:
  beamer:
    theme: monash
    aspectratio: 169
    fontsize: 14pt
    section-titles: false
    knitr:
      opts_chunk:
        dev: "cairo_pdf"
include-in-header: header.tex
execute:
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---

```{r setup, include=FALSE}
source("setup.R")
```

## Contact details

\vspace*{0.2cm}
\begin{alertblock}{Lecturer:  Professor Rob Hyndman}
\href{mailto:rob.hyndman@monash.edu}{\faicon{envelope}  rob.hyndman@monash.edu}

\href{https://robjhyndman.com}{\faicon{home} robjhyndman.com}

\href{https://twitter.com/robjhyndman}{\faicon{twitter} @robjhyndman}

%\href{https://robjhyndman.com}{\faicon{university} Room E762, Menzies Building}
\end{alertblock}

\begin{block}{Tutors}
\begin{itemize}\itemsep=0cm\parskip=0cm
\item \textbf{Mitchell O'Hara-Wild}
\item Elena Sanina
\item Xiaoqian Wang
\item Yangzhouran (Fin) Yang
\item Zhixiang (Elvis) Yang
\end{itemize}
\end{block}

## Brief bio
\fontsize{13}{16}\sf

  - Professor of Statistics, Monash University
  - Co-author of most popular forecasting textbook in the world
  - Developer of most popular forecasting software in the world

### How my forecasting methodology is used:
   - Pharmaceutical Benefits Scheme
   - Electricity demand
   - Australian tourism demand
   - Ageing population
   - COVID-19 cases
   - TAC large claims

## Unit objectives
\fontsize{13}{14}\sf

  1. To obtain an understanding of common statistical methods used in business and economic forecasting.
  2. To develop the computer skills required to forecast business and economic time series data;
  3. To gain insights into the problems of implementing and operating large scale forecasting systems for use in business.

### Teaching and learning approach

* Recorded lectures embedded in the textbook at [OTexts.com/fpp3](https://OTexts.com/fpp3)
* No scheduled activities on Monday (other than week 1)
* One 50 minute lecture each Wednesday for 12 weeks.
* One 80 minute tutorial each week for 12 weeks.

## Classes
\vspace*{0.2cm}

### Lectures

**Week 1**: Monday 11am in-person. Wednesday 3pm online

**Weeks 2--11**: Wednesday 3pm online

**Week 12**: Wednesday 3pm in-person

\pause

### Tutorials

* In-person unless you're overseas.

\pause

###

* All lectures will be recorded and posted on Moodle
* One tutorial will be recorded each week and posted on Moodle.

## Key reference

\begin{block}{}\bf
\hangafter=1\hangindent=.3cm
 {Hyndman, R.~J. \& Athanasopoulos, G. (2021) \emph{Forecasting: principles and practice}, 3rd edition}
\end{block}\pause
\begin{alertblock}{}\Large
\centerline{\bf OTexts.org/fpp3/}
\end{alertblock}

\pause

  * Free and online
  * Data sets in associated R packages
  * R code for examples

## Outline

\begin{tabular}{rp{8cm}l}
\textbf{Week} & \textbf{Topic}                      & \textbf{Chapter} \\
\midrule
1             & Introduction to forecasting and R   & 1 \\
2             & Time series graphics                & 2 \\
3             & Time series decomposition           & 3 \\
4             & The forecaster's toolbox            & 5\\
5--6          & Exponential smoothing               & 8  \\
7--9          & Forecasting with ARIMA models       & 9 \\
10--11        & Multiple regression and forecasting & 7 \\
11--12        & Dynamic regression                  & 10 \\
\end{tabular}

## Assessment
\vspace*{-0.2cm}

  - Four assignments and one larger project: 40%
  - Exam (2 hours): 60%.

\pause

\begin{block}{}\small\centering
\begin{tabular}{llr}
	  \textbf{Task}  & \textbf{Due Date}     & \textbf{Value} \\
  \midrule
    Assignment 1    & Sun 12 March & 2\% \\
    Assignment 2    & Sun 26 March & 6\% \\
    Assignment 3    & Sun 16 April & 6\% \\
    Assignment 4    & Sun 30 April & 6\% \\
    Project        & Sun 21 May            & 20\%           \\
	  Final exam     & Official exam period  & 60\%
\end{tabular}
\end{block}

\pause\vspace*{-0.4cm}

  - Need at least 45\% for exam, and 50\% for total.
  - \textbf{ETC5550 students:} Extra exam question.

## Moodle site
\fontsize{18}{24}\sf

  - Includes all course materials
  - Assignment submissions
  - Forum for asking questions, etc.

###
**Please don't send emails. Use the forum.**

## International Institute of Forecasters

\placefig{1}{3}{width=4cm}{iifLOGO2}

\begin{textblock}{8}(7,3)
  \begin{block}{}
  \begin{itemize}
  \item The IIF provides a prize to the top student in this subject each year.
  \item US\$100 plus one year membership.
  \end{itemize}
  \end{block}
\end{textblock}

## R
\fontsize{13}{13}\sf

![](figs/Rlogo.png){height=1.3cm}

Available for download from CRAN:

https://cran.r-project.org

\vspace*{-0.5cm}\noindent\rule{\textwidth}{1pt}

![](figs/RStudio-Logo-Flat.png){height=1.3cm}

Available for download from RStudio:

https://posit.co/download/rstudio-desktop/

<!-- \placefig{.4}{1.2}{width=6cm}{figs/Rlogo} -->

<!-- \placefig{7}{3.5}{width=5.5cm}{figs/RStudio-Ball} -->

## Main packages

\placefig{4.2}{1.4}{width=3.8cm}{tsibble.png}
\placefig{8.0}{1.4}{width=3.8cm}{tsibbledata.png}
\placefig{2.3}{4.65}{width=3.8cm}{tidyverse.png}
\placefig{6.1}{4.65}{width=3.8cm}{feasts.png}
\placefig{9.9}{4.65}{width=3.8cm}{fable.png}

## Main packages

```r
# Install required packages (do once)
install.packages(c("tidyverse", "fpp3"))
```

\pause

```r
# At the start of each session
library(fpp3)
```

## Exercises Week 1
\fontsize{18}{24}\sf

 * Make sure you are familiar with R, RStudio and the tidyverse packages.
 * Do first five chapters of `learnr.numbat.space`.
 * Assignment 1

## Assignment 1: forecast the following series
\small

  1. Google closing stock price in $USD on 20 March 2023.
  2. Maximum temperature at Melbourne airport on 4 April 2023.
  3. The difference in points (Collingwood minus Essendon) scored in the AFL match between Collingwood and Essendon for the Anzac Day clash. 25 April 2023.
  4. The seasonally adjusted estimate of total employment for April 2023. ABS CAT 6202, to be released around mid May 2023.
  5. Google closing stock price in $USD on 22 May 2023.

\begin{block}{Due Sunday 12 March}
For each of these, give a point forecast and an 80\% prediction interval.
\end{block}\pause
\begin{alertblock}{}
Prize: \$50 Amazon gift voucher
\end{alertblock}

## Assignment 1: scoring
\small

$Y=$ actual, $F=$ point forecast, $[L,U]=$ prediction interval

### Point forecasts:

$$\text{Absolute Error} = |Y-F|
$$\vspace*{-1cm}

 * Rank results for all students in class
 * Add ranks across all five items

### Prediction intervals:

$$
\text{Interval Score} = (U - L) + 10(L - Y)_+ + 10 (Y-U)_+
$$\vspace*{-1cm}

 * $u_+ = \text{max}(u,0)$
 * Rank results for all students
 * Add ranks across all five items