Visual Analytics for Development and Evaluation of Order Selection Criteria for Autoregressive Processes
Thomas Löwe, Emmy-Charlotte Förster, Geórgia Albuquerque, Jens‐Peter Kreiß, Marcus A. Magnor · IEEE Transactions on Visualization and Computer Graphics · 2015
Order selection of autoregressive processes is an active research topic in time series analysis, and the development and evaluation of automatic order selection criteria remains a challenging task for domain experts. We propose a visual analytics approach, to guide the analysis and development of such criteria. A flexible synthetic model generator-combined with specialized responsive visualizations-allows comprehensive interactive evaluation. Our fast framework allows feedback-driven development and fine-tuning of new order selection criteria in real-time. We demonstrate the applicability of our approach in three use-cases for two general as well as a real-world example.