Journal ArticleDOI
Understanding Computational Bayesian Statistics. W. M. Bolstad (2010). Hoboken, NJ, USA: Wiley. ISBN 978‐0‐470‐04609‐8.
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This article is published in Biometrical Journal.The article was published on 2011-05-01. It has received 4 citations till now. The article focuses on the topics: Bayesian statistics.read more
Citations
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Journal ArticleDOI
Bayesian Updating with Structural Reliability Methods
Daniel Straub,Iason Papaioannou +1 more
TL;DR: An algorithm for the implementation of BUS is proposed, which can be interpreted as an enhancement of the classic rejection sampling algorithm for Bayesian updating, and its efficiency is not dependent on the number of random variables in the model.
Journal ArticleDOI
Highly Efficient Probabilistic Finite Element Model Updating Using Intelligent Inference With Incomplete Modal Information
Kai Zhou,Jiong Tang +1 more
TL;DR: A highly efficient probabilistic framework of finite element model updating in the presence of measurement noise/uncertainty using intelligent inference is presented and is built upon the Bayesian inference approach.
Data-Adaptive Multivariate Density Estimation Using Regular Pavings, With Applications to Simulation-Intensive Inference
TL;DR: The semi-automatic convergence diagnosis method provides a useful improvement to the Markov chain Monte Carlo rp partitioning method, which is shown to work well in low dimensions and to have considerable potential for Bayesian inference for complex models with intractable likelihood functions.
Proceedings ArticleDOI
Quantification of Uncertainty in a Sediment Provenance Model
TL;DR: In this paper, the authors quantify and compare model uncertainty derived from sediment provenance or fingerprinting models using mathematical and statistical formulation rooted in the traditional Optimization and Bayesian Markov Chain Monte Carlo Simulation (MCMC) schemes.
References
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Journal ArticleDOI
Bayesian Updating with Structural Reliability Methods
Daniel Straub,Iason Papaioannou +1 more
TL;DR: An algorithm for the implementation of BUS is proposed, which can be interpreted as an enhancement of the classic rejection sampling algorithm for Bayesian updating, and its efficiency is not dependent on the number of random variables in the model.
Journal ArticleDOI
Highly Efficient Probabilistic Finite Element Model Updating Using Intelligent Inference With Incomplete Modal Information
Kai Zhou,Jiong Tang +1 more
TL;DR: A highly efficient probabilistic framework of finite element model updating in the presence of measurement noise/uncertainty using intelligent inference is presented and is built upon the Bayesian inference approach.
Journal ArticleDOI
Reliability as an Independent Variable Applied to Liquid Rocket Engine Test Plans
TL;DR: The reliability-as-an-independent-variable methodology as discussed by the authors is the solution proposed by expressing quantitatively the reliability trade space as ranges of a number of hardware sets and the number of hot-fire tests necessary to develop and qualify/certify a liquid rocket engine against a stated reliability requirement.
Data-Adaptive Multivariate Density Estimation Using Regular Pavings, With Applications to Simulation-Intensive Inference
TL;DR: The semi-automatic convergence diagnosis method provides a useful improvement to the Markov chain Monte Carlo rp partitioning method, which is shown to work well in low dimensions and to have considerable potential for Bayesian inference for complex models with intractable likelihood functions.
Hierarchical Bayesian Methods for Evaluation of Traffic Project Efficacy
TL;DR: Using the models selected for analysis, it was determined that cable barriers are quite effective at reducing severe crashes and cross-median crashes on Utah highways.