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Published in 2019 at "Metrika"
DOI: 10.1007/s00184-019-00737-2
Abstract: In this paper, we investigate Bayesian and robust Bayesian estimation of a wide range of parameters of interest in the context of Bayesian nonparametrics under a broad class of loss functions. Dealing with uncertainty regarding…
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Keywords:
dirichlet;
bayesian estimation;
robust bayesian;
general guide ... See more keywords
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Published in 2020 at "Control Engineering Practice"
DOI: 10.1016/j.conengprac.2020.104344
Abstract: Abstract In this paper, a novel robust Bayesian network is proposed for process modeling with low-quality data. Since unreliable data can cause model parameters to deviate from the real distributions and make network structures unable…
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Keywords:
quality;
robust bayesian;
process;
monitoring ... See more keywords
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Published in 2019 at "ASTIN Bulletin"
DOI: 10.1017/asb.2018.36
Abstract: Abstract We study the propagation of uncertainty from a class of priors introduced by Arias-Nicolás et al. [(2016) Bayesian Analysis, 11(4), 1107–1136] to the premiums (both the collective and the Bayesian), for a wide family…
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Keywords:
bands prior;
bayesian premiums;
deriving robust;
robust bayesian ... See more keywords
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Published in 2021 at "IISE Transactions"
DOI: 10.1080/24725854.2021.1912440
Abstract: Abstract Empirical models that relate multiple quality features to a set of design variables play a vital role in many industrial process optimization methods. Many of the current modeling methods employ a single-response normal model…
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Keywords:
bayesian hierarchical;
inference using;
modeling inference;
hierarchical modeling ... See more keywords
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Published in 2019 at "Statistical Methods in Medical Research"
DOI: 10.1177/0962280218820040
Abstract: Before a first-in-man trial is conducted, preclinical studies are performed in animals to help characterise the safety profile of the new medicine. We propose a robust Bayesian hierarchical model to synthesise animal and human toxicity…
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Keywords:
phase;
robust bayesian;
animal species;
toxicity ... See more keywords
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Published in 2018 at "AIAA Journal"
DOI: 10.2514/1.j057204
Abstract: Compressible jet-in-crossflow interactions are difficult to simulate accurately using Reynolds-averaged Navier–Stokes (RANS) models. This could be due to simplifications inherent in RANS or the use...
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Keywords:
compressible jet;
robust bayesian;
bayesian calibration;
calibration model ... See more keywords
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Published in 2021 at "Statistica Sinica"
DOI: 10.5705/ss.202018.0063
Abstract: We study robust Bayesian prediction problems using the posterior regret Γ-minimax (PRGM) approach. We provide a unified theory for PRGM prediction under a very general class of regret loss functions that includes squared error (SE),…
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Keywords:
bayesian prediction;
class;
robust bayesian;
loss functions ... See more keywords