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

@article{Lwe2016VisualAF,
  title={Visual Analytics for Development and Evaluation of Order Selection Criteria for Autoregressive Processes},
  author={Thomas L{\"o}we and Emmy-Charlotte F{\"o}rster and Georgia Albuquerque and Jens-Peter Kreiss and Marcus A. Magnor},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  year={2016},
  volume={22},
  pages={151-159}
}
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… 
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