A Nonparametric Bayesian Framework for Uncertainty Quantification in Stochastic Simulation

A Nonparametric Bayesian Framework for Uncertainty Quantification in Stochastic Simulation

10.1137/20m1345517

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Bibliographic Details
Main Authors: Xie, Wei, LI CHENG, Wu, Yuefeng, Zhang, Pu
Other Authors: STATISTICS AND DATA SCIENCE
Format: Article
Published: Society for Industrial & Applied Mathematics (SIAM) 2022
Subjects:
nonparametric Bayesian approach
design of experiments
stochastic simulation
Uncertainty quantification
input uncertainty
Dirichlet process mixtures
Online Access:https://scholarbank.nus.edu.sg/handle/10635/217276
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Institution: National University of Singapore

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https://scholarbank.nus.edu.sg/handle/10635/217276

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