Results 21 to 30 of about 11,544,586 (297)
Bayesian quantification of thermodynamic uncertainties in dense gas flows [PDF]
, 2014 A Bayesian inference methodology is developed for calibrating complex equations of state used in numerical fluid flow solvers. Precisely, the input parameters of three equations of state commonly used for modeling the thermodynamic behavior of so-called ...
CINNELLA, Paola, X. Merle, MERLE, Xavier
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Approximate Bayesian Inference Based on Expected Evaluations [PDF]
, 2023 Approximate Bayesian computing (ABC) and Bayesian Synthetic likelihood (BSL) are two popular families of methods to evaluate the posterior distribution when the likelihood function is not available or tractable.
Hammer, Hugo Lewi, Riegler, Michael
core
Frontiers in Psychology, 2020 One practical challenge in observational studies and quasi-experimental designs is selection bias. The issue of selection bias becomes more concerning when data are non-normal and contain missing values.
Dingjing Shi +3 more
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Bayesian back analysis considering constraints
Yantu gongcheng xuebao, 2021 Soil parameters significantly affect the prediction performance of geotechnical models. In the field of parameter identification, the MCMC-based Bayesian method is an effective way to infer the probability distribution of soil parameters.
TAO Yuan-qin 1 , SUN Hong-lei 2, CAI Yuan-qiang 1, 2
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Bayesian assessment of the prevalence of BRCA-associated breast cancer in Moscow
Alʹmanah Kliničeskoj Mediciny, 2020 Rationale: For many years, breast cancer has been leading in the cancer structure in women, accounting for 21% from the total number of newly diagnosed cases of malignancies in Russia. The literature on the prevalence of the BRCA-associated breast cancer
A. V. Viskovatykh
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Approximate Bayesian inference for doubly robust estimation [PDF]
, 2015 Doubly robust estimators are typically constructed by combining outcome regression and propensity score models to satisfy moment restrictions that ensure consistent estimation of causal quantities provided at least one of the component models is ...
McCoy, EJ, Graham, DJ, Stephens, DA
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Bayes Estimation of Shape Parameter of Length Biased Weibull Distribution
JTAM (Jurnal Teori dan Aplikasi Matematika), 2021 In this paper, length biased Weibull distribution is considered for Bayesian analysis. The expressions for Bayes estimators of the parameter have been derived under squared error, precautionary, entropy, K-loss, and Al-Bayyati’s loss functions by using ...
Arun Kumar Rao, Himanshu Pandey
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Approximate Bayesian computational methods [PDF]
Statistics and Computing, 2011 7 ...
Jean-Michel Marin +3 more
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Bayesian Solution Uncertainty Quantification for Differential Equations [PDF]
, 2016 We explore probability modelling of discretization uncertainty for system states defined implicitly by ordinary or partial differential equations. Accounting for this uncertainty can avoid posterior under-coverage when likelihoods are constructed from a ...
Girolami, MA +4 more
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Comparative study on the influence of rain-gauge network on the uncertainty of hydrological modeling
Shui kexue jinzhan, 2019 The design of the rain gauge network affects the accuracy of model simulation. Therefore,studying the effect of rain gauge density and its distribution on improving runoff simulation accuracy and reducing the modeling uncertainty is of vital importance ...
CHEN Hua +6 more
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