Quantify uncertainty by estimating the probability density function of the output of interest using MLMC based Bayes method

DOI10.3934/dcdsb.2022095OpenAlexW4285108519MaRDI QIDQ2083326

Meixin Xiong, Liuhong Chen, Ju Ming

Publication date: 10 October 2022

Published in: Discrete and Continuous Dynamical Systems. Series B (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3934/dcdsb.2022095

zbMATH Keywords

Bayes estimatorvariance reductionprobability distribution functionuncertainty quantificationmultilevel Monte Carlo

Mathematics Subject Classification ID

Density estimation (62G07) Bayesian inference (62F15) Monte Carlo methods (65C05) PDEs with randomness, stochastic partial differential equations (35R60)

Uses Software

• Wesseling

Cites Work

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