The effect of prior probabilities on quantification and propagation of imprecise probabilities resulting from small datasets

DOI10.1016/j.cma.2018.01.045zbMath1440.62099arXiv1710.03294OpenAlexW2763138175MaRDI QIDQ2310925

Jiaxin Zhang, Michael D. Shields

Publication date: 7 April 2020

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1710.03294

zbMATH Keywords

Bayesian inferenceimprecise probabilityuncertainty quantificationdata-drivenmultimodel inferenceprior probabilities

Mathematics Subject Classification ID

Bayesian inference (62F15) Computational methods for problems pertaining to probability theory (60-08)

Related Items (6)

On the quantification and efficient propagation of imprecise probabilities with copula dependence ⋮ Uncertainty quantification in multiscale simulation of woven fiber composites ⋮ Bounds optimization of model response moments: a twin-engine Bayesian active learning method ⋮ A copula-based uncertainty propagation method for structures with correlated parametric p-boxes ⋮ The effect of prior probabilities on quantification and propagation of imprecise probabilities resulting from small datasets ⋮ PhyCRNet: physics-informed convolutional-recurrent network for solving spatiotemporal PDEs

Uses Software

• DDDAS
• emcee

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