This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Rob J Hyndman is Professor of Statistics at Monash University, Australia, and Editor-in-Chief of the International Journal of Forecasting. He is author of over 150 research papers in statistical science. In 2007, he received the Moran medal from the Australian Academy of Science for his contributions to statistical research. For over 30 years, Rob has maintained an active consulting practice, assisting hundreds of companies and organizations on forecasting problems.
George Athanasopoulos is an Associate Professor in the Department of Econometrics and Business Statistics at Monash University, Australia. He received a PhD in Econometrics from Monash University in 2007, and has received many awards and distinctions for his research. His research interests include multivariate time series analysis, forecasting, non-linear time series, wealth and tourism economics. He is on the Editorial Boards of the Journal of Travel Research and the International Journal of Forecasting.
Rob J Hyndman is Professor of Statistics at Monash University, Australia. He was a Christadelphian for nearly 30 years, and was well-known as a writer and Bible teacher within the Christadelphian community. He gave up Christianity when he no longer thought that there was sufficient evidence to support belief in the Bible.
This is a personal memoir describing Rob's journey of deconversion. Until recently, he was regularly speaking at church conferences internationally, and his books are still used in Bible classes and Sunday Schools around the world. He even helped establish an innovative new church, which became a model for similar churches in other countries. Eventually he came to the view that he was mistaken, and that there was little or no evidence that the Bible was inspired or that God exists.
In this book, he reflects on how he was fooled, and why he changed his mind. Whether you agree with his conclusions or not, you will be led to reflect on the nature of faith and evidence, and how they interact.
Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
The book is written for undergraduate students of mathematics, economics, business and finance, geography, engineering and related disciplines, and postgraduate students who may need to analyse time series as part of their taught programme or their research.