Description:
In this webinar, we’ll discuss how to go beyond time series modeling by augmenting statistical forecasts with external information that can predict facets of future demand better than historic data alone.
We’ll explore what kinds of forecasting are best suited to Multivariate Modeling and how to set up your Forecast Pro project to utilize it. Topics include:
● What is Dynamic Regression? How does it differ from time series forecasting?
● How to assemble a regression model in Forecast Pro
● Setting up external variables for regression analysis
● Interpreting statistics and improving your Dynamic Regression model over time
● External variables’ interplay with Machine Learning
New and experienced Forecast Pro users alike will benefit from this in depth discussion of a modeling methodology that links together multiple data sources to fine tune statistical forecasts.
We will present this webinar twice to accommodate attendees in various time zones. Completing the registration allows you to attend either session.
Can’t attend the live webinar? Register for the session and we will notify you via email when the recording is available for on-demand viewing.
Speaker:
James Berry has
