Results 21 to 30 of about 12,151,236 (300)
Simulation-Based Calibration Checking for Bayesian Computation: The Choice of Test Quantities Shapes Sensitivity [PDF]
, 2023 Simulation-based calibration checking (SBC) is a practical method to validate computationally-derived posterior distributions or their approximations. In this paper, we introduce a new variant of SBC to alleviate several known problems.
Shinyoung, Kim +9 more
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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
doaj +1 more source
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
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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
openaire +5 more sources
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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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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Hangkong gongcheng jinzhan, 2022 Bayesian method is commonly used in the reliability assessment of repairable systems with small samples in fields such as aerospace.The knowledge about the informative prior and/or failure data from repairable systems may not be collected as precisely as
WANG Yanping, WEIYupeng, LYU Zhenzhou
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Bayesian Varying-coefficient Models using Adaptive Regression Splines [PDF]
, 2000 Varying-coefficient models provide a flexible framework for semi- and nonparametric generalized regression analysis. We present a fully Bayesian B-spline basis function approach with adaptive knot selection.
Ludwig Fahrmeir +3 more
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