Workshop Title: Time Series Analysis: Part I

Workshop Description:

Time series analysis is an important area in statistics, data science and econometrics. A time series is a set of observations which are recorded sequentially over time. Time series data appear in diverse fields including, but not limited to, actuarial science, biological science, business analytics, climate science, computer science, cognitive science, economics, ecology, environmental science, finance, hydrology, and medical science. The analysis of time series data provides important insights into knowledge discovery and making predictions.

This workshop aims to provide a basic introduction to the use of R for analysing real time series data. Attention will be given to linear time series models such as autoregressive (AR) models, moving average (MA) models, autoregressive moving average (ARMA) models, and autoregressive integrated moving average (ARIMA) models. The use of the Box–Jenkins method for linear time series model building will be considered. Some concepts and mathematics underlying linear time series analysis will be briefly discussed. Knowledge of basic probability and statistics will be assumed. Prior knowledge of linear models and time series analysis will be great.

Presenter:

Dr Ken Siu is a Professor in the Department of Acturial Studies and Business Analytics at Macquarie University. Ken's research interests are Mathematical Finance, Actuarial Science, Quantitative Risk Management, Applications of Stochastic Processes, Filtering and Control, Applied Probability and Statistics.

Workshop Resources:

The resources for this workshop will be available soon from https://github.com/mqRusers. Please have R and R Studio downloaded on your laptop before the workshop. You can find instructions for the installation here: https://rstudio-education.github.io/hopr/starting.html.

The data set used in the workshop can be found here: https://fred.stlouisfed.org/series/TB3MS