Computer Graphics
TU Braunschweig

Visual Analytics for Development and Evaluation of Order Selection Criteria for Autoregressive Processes


Visual Analytics for Development and Evaluation of Order Selection Criteria for Autoregressive Processes

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.


Author(s):Thomas Löwe, Emmy-Charlotte Förster, Georgia Albuquerque, Jens-Peter Kreiß, Marcus Magnor
Year:2016
Month:January
Type:Article
Journal:IEEE Transactions on Visualization and Computer Graphics (TVCG) Vol. 22
Note:IEEE VIS 2015 paper
Project(s): Scalable Visual Analytics 


@article{loewe2015osc,
  title = {Visual Analytics for Development and Evaluation of Order Selection Criteria for Autoregressive Processes},
  author = {L{\"o}we, Thomas and F{\"o}rster, Emmy-Charlotte and Albuquerque, Georgia and Krei{\ss}, Jens-Peter and Magnor, Marcus},
  journal = {{IEEE} Transactions on Visualization and Computer Graphics ({TVCG})},
  volume = {22},
  number = {1},
  note = {{IEEE} {VIS} 2015 paper},
  pages = {151--159},
  month = {Jan},
  year = {2016}
}

Authors