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Versatile sequential sampling algorithm using kernel density estimation

Author
Roy, P.; Jofre, L.
Type of activity
Journal article
Journal
European journal of operational research
Date of publication
2020-07-01
Volume
284
Number
1
First page
201
Last page
211
DOI
10.1016/j.ejor.2019.11.070
Repository
http://hdl.handle.net/2117/187283 Open in new window
URL
https://doi.org/10.1016/j.ejor.2019.11.070 Open in new window
Abstract
Understanding the physical mechanisms governing scientific and engineering systems requires performing experiments. Therefore, the construction of the Design of Experiments (DoE) is paramount for the successful inference of the intrinsic behavior of such systems. There is a vast literature on one-shot designs such as low discrepancy sequences and Latin Hypercube Sampling (LHS). However, in a sensitivity analysis context, an important property is the stochasticity of the DoE which is partially ad...
Citation
Roy, P.; Jofre, L. Versatile sequential sampling algorithm using kernel density estimation. "European journal of operational research", 1 Juliol 2020, vol. 284, no 1 p. 201-211.
Keywords
Design of experiments, Discrepancy, Optimal design, Stochastic processes, Uncertainty quantification

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