Abstract
Providing assistance systems for simulation studies can support the user by performing monotonous tasks and keeping track of relevant results. In this paper we present approaches to estimate, if – and when – statistically significant results are expected for certain investigations. This information can be used to control simulation runs or to provide information to the user for interaction. The first approach is used to classify if significance is expected to occur for given samples and the second approach estimates the needed replications until significance is expected be reached. For an initial evaluation of the approaches, experiments are performed on samples drawn from normal distributions.
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Lattner, A.D., Bogon, T., Timm, I.J. (2013). Convergence Classification and Replication Prediction for Simulation Studies. In: Filipe, J., Fred, A. (eds) Agents and Artificial Intelligence. ICAART 2011. Communications in Computer and Information Science, vol 271. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29966-7_17
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DOI: https://doi.org/10.1007/978-3-642-29966-7_17
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