Forecast Reconciliation Made Easy: The FoReco Package - Daniele Girolimetto

Daniele Girolimetto is a postdoctoral researcher in the Department of Statistical Sciences at the University of Padova. His research interests are related to time series including statistical methods (univariate/multivariate forecasting approaches, bootstrap methods, applications in finance, energy, and economics), computational statistics (developing efficient algorithms and software), and modern approaches like machine learning and deep learning.