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- W4254196677 abstract "The density of stochastic simulation output provides more information on system performance than the mean alone. However, density estimation methods may require large sample sizes to achieve a certain accuracy or desired structural properties. A nonparametric estimation method based on exponential epi-splines has shown promise to overcome this difficulty by incorporating qualitative and quantitative information that reduces the space of possible density estimates substantially. Such `soft' information may come in the form of the knowledge of a non-negative support, unimodality, and monotonicity, and is often available in simulation applications. We examine this method for output analysis of stochastic systems with fixed input parameters, and for a model with stochastic input parameters, with an emphasis on the use of derivative information." @default.
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- W4254196677 date "2013-12-01" @default.
- W4254196677 modified "2023-09-23" @default.
- W4254196677 title "Density estimation of simulation output using exponential epi-splines" @default.
- W4254196677 doi "https://doi.org/10.1109/wsc.2013.6721468" @default.
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