The Influence Explorer (video)—a tool for design
Conference Companion on Human Factors in Computing Systems
Design galleries: a general approach to setting parameters for computer graphics and animation
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
CHI '94 Conference Companion on Human Factors in Computing Systems
Interactive data visualization using focusing and linking
VIS '91 Proceedings of the 2nd conference on Visualization '91
ANSS '07 Proceedings of the 40th Annual Simulation Symposium
Scented Widgets: Improving Navigation Cues with Embedded Visualizations
IEEE Transactions on Visualization and Computer Graphics
Large-Scale Design Space Exploration of SSA
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
Handbook of Parametric and Nonparametric Statistical Procedures
Handbook of Parametric and Nonparametric Statistical Procedures
Revealing uncertainty for information visualization
Information Visualization
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Result-Driven Exploration of Simulation Parameter Spaces for Visual Effects Design
IEEE Transactions on Visualization and Computer Graphics
Streamlined formulation of adaptive explicit-implicit tau-leaping with automatic tau selection
Winter Simulation Conference
Visualization of Parameter Space for Image Analysis
IEEE Transactions on Visualization and Computer Graphics
Divergence measures based on the Shannon entropy
IEEE Transactions on Information Theory
Visualizing summary statistics and uncertainty
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
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Visual Analytics offers various interesting methods to explore high dimensional data interactively. In this paper we investigate how it can be applied to support experimenters and developers of simulation software conducting simulation studies. In particular the usage and development of approximate simulation algorithms poses several practical problems, e.g., estimating the impact of algorithm parameters on accuracy or detecting faulty implementations. To address some of those problems, we present an approach that allows to relate configurations and accuracy visually and exploratory. The approach is evaluated by a brief case study, focusing on the accuracy of Stochastic Simulation Algorithms.