Statistics Across Campuses: Rob J Hyndman -- The geometry of forecast reconciliation

The geometry of forecast reconciliation 

Date: Friday 28 August 2020 

Time: 3 pm 

Speaker: Prof Rob J Hyndman (Monash University) 

Abstract: 

It is common to forecast at different levels of aggregation.  For example, a retail
company will want national forecasts, state forecasts, and store-level forecasts.  And
they will want them for all products, for groups of products, and for individual
products.  Forecast reconciliation methods allow for the forecasts at all levels of
aggregation to be adjusted so they are consistent with each other.  

I will describe a geometric interpretation for reconciliation methods used to forecast
time series that adhere to known linear constraints.  In particular, a general framework
is established nesting many existing popular reconciliation methods within the class of
projections.  This interpretation facilitates the derivation of novel results that
explain why and how reconciliation via projection is guaranteed to improve forecast
accuracy with respect to a specific class of loss functions.  The result is also
demonstrated empirically using Australian tourism flows.  I will also discuss how this
geometric interpretation naturally extends to probabilistic forecasting.  Finally, I
will show how these ideas can be easily implemented using the fable package in R.  

Zoom Link: https://macquarie.zoom.us/j/98585371451?pwd=bTFxWVZ2RWcvK2tmblVYMGVjdG9sQT09