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   Articles with "robust bayesian" as a keyword



A general guide in Bayesian and robust Bayesian estimation using Dirichlet processes

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recommendations! 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… read more here.

Keywords: dirichlet; bayesian estimation; robust bayesian; general guide ... See more keywords
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Robust Bayesian networks for low-quality data modeling and process monitoring applications

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recommendations! 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… read more here.

Keywords: quality; robust bayesian; process; monitoring ... See more keywords
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DERIVING ROBUST BAYESIAN PREMIUMS UNDER BANDS OF PRIOR DISTRIBUTIONS WITH APPLICATIONS

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recommendations! 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… read more here.

Keywords: bands prior; bayesian premiums; deriving robust; robust bayesian ... See more keywords

Robust Bayesian hierarchical modeling and inference using scale mixtures of normal distributions

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recommendations! 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… read more here.

Keywords: bayesian hierarchical; inference using; modeling inference; hierarchical modeling ... See more keywords

Double-robust Bayesian variable selection and model prediction with spherically symmetric error

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recommendations! Published in 2025 at "IISE Transactions"

DOI: 10.1080/24725854.2025.2491492

Abstract: Abstract Response surface methodology has been known to be an effective tool for improving an overall manufacturing process where quality requirements are fulfilled. This work proposes a double-robust Bayesian modeling method that can simultaneously cope… read more here.

Keywords: variable selection; double robust; prediction; model ... See more keywords

A robust Bayesian meta-analytic approach to incorporate animal data into phase I oncology trials

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recommendations! 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… read more here.

Keywords: phase; robust bayesian; animal species; toxicity ... See more keywords
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Robust Bayesian Calibration of a k−ε Model for Compressible Jet-in-Crossflow Simulations

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recommendations! 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... read more here.

Keywords: compressible jet; robust bayesian; bayesian calibration; calibration model ... See more keywords

A Unified Theory for Robust Bayesian Prediction Under a General Class of Regret Loss Functions

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recommendations! 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),… read more here.

Keywords: bayesian prediction; class; robust bayesian; loss functions ... See more keywords