Automating Vector Autoregression on Electronic Patient Diary Data

—Finding the best vector autoregression model for any data set, medical or otherwise, is a process that, to this day, is frequently performed manually in an iterative manner requiring statistical expertise and time. Very few software solutions for automating this process exist and they still require statistical expertise to operate. We propose a new application called Autovar for the automation of finding vector autoregression models for time series data. The approach closely resembles the way in which experts work manually. Our proposal offers improvements over the manual approach by leveraging computing power, e.g., by considering multiple alternatives instead of choosing just one. In this paper, we describe the design and implementation of Autovar, we compare its performance against experts working manually, and we compare its features to those of the most used commercial solution available today. The main contribution of Autovar is to show that vector autoregression on a large s...

• Type: Journal
• Year: 2016
• Where: TITB
• Authors: Ando Celino Emerencia, Lian van der Krieke, Elisabeth H. Bos, Peter de Jonge, Nicolai Petkov, Marco Aiello 0001
• Keywords: Education, TITB 2016