[PDF] Top 20 On the use of Bayesian Monte-Carlo in evaluation of nuclear data
Has 10000 "On the use of Bayesian Monte-Carlo in evaluation of nuclear data" found on our website. Below are the top 20 most common "On the use of Bayesian Monte-Carlo in evaluation of nuclear data".
On the use of Bayesian Monte-Carlo in evaluation of nuclear data
... One important point is that these methods could be used for resonance range analysis (both resolved and unresolved resonance) as well as higher energy models. In addition, both microscopic integral data ... See full document
6
Efficient use of Monte Carlo: the fast correlation coefficient
... Monte Carlo (MC) (or random sampling) methods are frequently used for nuclear data (ND) evaluation and uncertainty ...Total Monte Carlo (TMC), method is used where the ... See full document
5
On the use of the BMC to resolve Bayesian inference with nuisance parameters
... the evaluation of nuclear data: theoretical models, microscopic and integral ...to Bayesian parameters ...the Bayesian inference and a method using Monte-Carlo ...the ... See full document
8
Monte Carlo integral adjustment of nuclear data libraries – experimental covariances and inconsistent data
... As mentioned previously there are many reasons for the data to be inconsistent, both among the different experiments and between the experiments and the calculation. Many of these underlying causes can be treated ... See full document
7
Examples of Monte Carlo techniques applied for nuclear data uncertainty propagation
... of Monte Carlo techniques in the procedure of evaluation of nuclear ...assess nuclear data trends and determine the main contributors and uncertainty targets for the ... See full document
7
New Dosimetric Interpretation of the DV50 Vessel-Steel Experiment Irradiated in the OSIRIS MTR Reactor Using the Monte-Carlo Code TRIPOLI-4®
... In this paper, we present a new dosimetric interpretation of the DV50 experiment performed by using the Monte-Carlo code TRIPOLI-4 and more recent nuclear data (JEFF3.1.1 and IRDF-2002). ... See full document
9
Bayesian model comparison via sequential Monte Carlo
... Real data results Finally, the methodology of smc2-ps was applied to measured positron emission tomography data using the same compartmental setup as in the ...The data that lead to the 𝑉 𝐷 ... See full document
241
Geostatistical approach to bayesian inversion of geophysical data: Markov chain Monte Carlo method
... Geostatistics was originally devised to estimate properties of unsampled points for delineating ore deposits. But these days those tools are used not only for estimation of unsam- pled points but also for inference of ... See full document
15
A Bayesian Monte-Carlo Uncertainty Model for Assessment of Shear Stress Entropy
... a Bayesian procedure as Generalized Likelihood Uncertainty Estimation (GLUE) to measure uncertainties for a simple model of the rainfall-runoff ...the Bayesian Recursive Estimation (BaRE) to evaluate the ... See full document
47
Comparison with simulations to experimental data for photo-neutron reactions using SPring-8 Injector
... the Monte Carlo code ...both Monte Carlo codes. However experimental data, especially photonuclear reaction data are quite insufficient to compare to the ... See full document
6
Stochastic gradient Markov chain Monte Carlo
... these data using Bayesian probabilistic matrix factorisation (BPMF) (Salakhutdinov and Mnih, 2008), where the preference matrix of user-item ratings is factorised into lower-dimensional matrices ... See full document
31
A fully Bayesian approach to shape estimation of objects from tomography data using MFS forward solutions
... a Bayesian perspective of inverse ...the use of the finite element ...Then, Bayesian statistical modelling will be dis- cussed with specific examples given and an outline of the Markov chain ... See full document
22
Comparison of the Bayesian Methods on Interval Censored Data for Weibull Distribution
... and Bayesian with help of the Lindley’s approximation and Markov Chain Monte Carlo, where the Metropolis-Hastings algorithm used to estimate the scale and shape parameters, the mean squared errors ... See full document
9
Bayesian Ecometrics – A genial device to ponder Ecological Data Analysis
... particular, Bayesian analyses for complicated models can be carried out on a fixed data set relatively simple using Monte Carlo methods to simulate posterior ...distributions. Monte ... See full document
7
A Comparative Study of Slam Algorithms for Indoor Navigation of Autonomous Wheelchairs.
... incoming data from these sensors and build a map through observing envi- ronment, learning landmarks, and simultaneously estimating the location of the moving platform in that map with respect to the ... See full document
77
Bayesian Analysis
... applied Bayesian work needed to develop their own MCMC algorithms and write their own ...for Bayesian updating using Gibbs sampling. To use BUGS, one writes down a model definition using an R‐like ... See full document
13
Bayesian InferenceA pproach to Inverse P roblems in aFi nancial MathematicalM odel
... The method presented here can be extended in several ways. Our immediate future work will statistically apply the Tikhonov regularization method to IOP. As the hierarchical Bayesian method is analogous to the ... See full document
14
A Survey of Probabilistic Models Using the Bayesian Programming Methodology as a Unifying Framework
... cursive Bayesian Estimation, Bayesian Filters (BFs), Particle Filters (PFs), Markov Localization mod- els, Monte Carlo Markov Localization (MCML), and (Partially Observable) Markov Decision ... See full document
8
Exploring the Association between Network, Cognitive, Structural Social Capital and the Risk of Clinical Depression in Taiwan
... When data are truly generated according to an exchangeable Gaussian frailty PH model or the model of Liu et ...cancer data, and demonstrate that higher degree of ruralness corresponds to a more bimodal ... See full document
235
Measurements of diboson production with the ATLAS detector
... comparing data (full circles) to Monte Carlo (histograms): the presence of three leptons in the final states reduces most of the backgrounds, making possible to relax the lepton p T cuts with respect ... See full document
12
Related subjects