Ensemble Forecasts with {fable} by Dr. Rob J. Hyndman. Visit rstats.ai/nyr/ to learn more.
Abstract:
For over 50 years we have known that ensemble forecasts perform better than individual methods, yet they are not as widely used as they should be. Perhaps this is because users think it is more work, or that it is hard to get prediction intervals, or that it is difficult to determine the relative weights of the component methods. The fable package solves these problems and makes it easy to produce
Bio:
Dr. Rob J Hyndman is Professor of Statistics and Head of the Department of Econometrics and Business Statistics at Monash University. From 2005 to 2018 he was Editor-in-Chief of the International Journal of Forecasting and a Director of the International Institute of Forecasters. Rob is the author of over 200 research papers and 5 books in statistical science. In 2007, he received the Moran medal from the Australian Academy of Science for his contributions to statistical research, especially in the area of statistical forecasting. For over 30 years, Rob has maintained an active consulting practice, assisting hundreds of companies and organizations around the world. He has won awards for his research, teaching, consulting and graduate supervision.
Twitter: / robjhyndman
Presented at the 2020 R Conference | New York (August 14th, 2020)