Results 11 to 20 of about 2,159,110 (277)
Variance reduction in MCMC [PDF]
, 2003 We propose a general purpose variance reduction technique for MCMC estimators. The idea is obtained by combining standard variance reduction principles known for regular Monte Carlo simulations (Ripley, 1987) and the Zero-Variance principle introduced in
Bressanini Dario +2 more
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Choosing Transport Events for Initiating Splitting and Rouletting
Journal of Nuclear Engineering, 2021 A study was performed to determine which transport events should be used to initiate a weight window lookup to achieve the best variance reduction performance.
Evan S. Gonzalez, Gregory G. Davidson
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TOWARDS ZERO-VARIANCE SCHEMES FOR KINETIC MONTE-CARLO SIMULATIONS [PDF]
EPJ Web of Conferences, 2021 The solution of the time-dependent transport problem for neutrons and precursors in a nuclear reactor is hard to treat in a naive Monte-Carlo framework because of the largely different time scales associated to the prompt-fission chains and to the decay ...
Mancusi Davide, Zoia Andrea
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ROBUST SIMULATION METHOD OF COMPLEX TECHNICAL TRANSPORT SYSTEMS [PDF]
Transport Problems, 2021 In the optimization of technical systems focused on a specific functional purpose (reliability, safety, and availability) with the use of simulation methods, an important parameter is the digital simulation time of the research subject.
Janusz SZPYTKO, Yorlandys SALGADO DUARTE
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IMPLEMENTATION OF MONTE CARLO MOMENT MATCHING METHOD FOR PRICING LOOKBACK FLOATING STRIKE OPTION
Barekeng, 2022 Monte Carlo method was a numerical method that was popular in finance. This method had disadvantages at convergences, so the moment matching was used to improve the efficiency from Monte Carlo method.
Komang Nonik Afsari Dewi +2 more
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Pilot development: an empirical mixed-method analysis [PDF]
Journal of Defense Analytics and Logistics, 2022 Purpose – Pilot upgrade training is critical to aircraft and passenger safety. This study aims to identify variances in the US Air Force C-130J pilot upgrade training based on geographic location and provide a model to enhance policy that will impact ...
Jonathan Slottje +3 more
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Generalizing the Balance Heuristic Estimator in Multiple Importance Sampling
Entropy, 2022 In this paper, we propose a novel and generic family of multiple importance sampling estimators. We first revisit the celebrated balance heuristic estimator, a widely used Monte Carlo technique for the approximation of intractable integrals.
Mateu Sbert, Víctor Elvira
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INVESTIGATION ON DETERMINISTIC TRUNCATION TO CONTINUOUS ENERGY MONTE CARLO NEUTRON TRANSPORT CALCULATION [PDF]
EPJ Web of Conferences, 2021 This paper presents the application and evaluation of a deterministic truncation of Monte Carlo (DTMC) solution method in a whole core reactor problem based on a continuous energy transport calculation. The DTMC method has been studied and developed as a
Kim Inhyung, Kim Yonghee
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Statistical Theory and Related Fields, 2023 This paper deals with the Monte Carlo Simulation in a Bayesian framework. It shows the importance of the use of Monte Carlo experiments through refined descriptive sampling within the autoregressive model $ X_{t}=\rho X_{t-1}+Y_{t} $ , where $ 0 \lt \rho
Djoweyda Ghouil, Megdouda Ourbih-Tari
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A Flexible Stochastic Multi-Agent ADMM Method for Large-Scale Distributed Optimization
IEEE Access, 2022 While applying stochastic alternating direction method of multiplier (ADMM) methods has become enormously potential in distributed applications, improving the algorithmic flexibility can bring huge benefits.
Lin Wu, Yongbin Wang, Tuo Shi
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