Introduction

STAT 443:
Forecasting
Reza
Ramezan
Introduction
Examples

STAT 443: Forecasting
Fall 2012
Reza Ramezan [e-mail] M3 3144

STAT 443:
Forecasting

Timetable

Reza
Ramezan
Introduction
Examples

The following is a tentative schedule:
Week
Jan. 07
Jan. 14
Jan. 21
Jan. 28
Feb. 04
Feb. 11
Feb. 18
Feb. 25
Mar. 04
Mar. 11
Mar. 18
Mar. 25
Apr. 01

Course Material
Introduction
Regression
Regression
Smoothing / linear processes linear processes
Case study
Reading Week
Box-Jenkins Models
Box-Jenkins / Case study
Algorithms
Algorithms / Forecasting
Forecasting / Case study
ARCH / GARCH models

Deadlines

Assignment 1 (4th Feb.)
Midterm (15th Feb.)

Assignment 2 (15th Mar.)

Assignment 3 (8th Apr.)

STAT 443:
Forecasting

R

Reza
Ramezan
Introduction
Examples

• One of the aims of the course is to become fluent in the

computation associated with forecasting
• In this course R will be the language used for

computation
• Assignments will need coding in R
• In Exams you will be expected to interpret R output

STAT 443:
Forecasting

The Candy Rule

Reza
Ramezan
Introduction
Examples

The candy rule states that:
• If you answer questions about the course material I ask

during lectures, or ask good questions, you get candy.
• If I forget to give you one, you STAND UP FOR IT.

There are no stupid questions to ask. This is a class to learn. If you don’t know it, ask it.

STAT 443:
Forecasting

Forecasting

Reza
Ramezan
Introduction
Examples

• Why forecast?
• Why understand uncertainty of forecast?
• What information to use in forecast?

STAT 443:
Forecasting

Example: Accidental deaths

Reza
Ramezan
Introduction
Examples

• Many examples are time series– forecast what

happens in future
• Example: monthly number of accidental deaths in USA-

1973-79
• Look at structure of data

STAT 443:
Forecasting

Example: Accidental deaths