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Bayesian statistics and Monte Carlo methods
Journal of Geodetic Science, 2018 The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability.
Koch K. R.
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A comparative study between Classical Numerical Methods and Monte Carlo Methods [PDF]
المجلة العراقية للعلوم الاحصائية, 2008 Recently, there is a great interest in the methods of Monte Carlo used for the treatment of different technical and scientific issues. This research deals with using the Monte Carlo methods in numerical integration by making a general comparison between
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An LPC pole processing method for enhancing the identification of dominant spectral features
Electronics Letters, 2021 This paper proposes a new time‐resolved spectral analysis method based on a modification to the linear predictive coding (LPC) method for enhancing the identification of the dominant frequencies of a signal.
Jin Xu, Mark Davis, Ruairí de Fréin
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Monte Carlo Methods for the Shapley–Shubik Power Index
Games, 2022 This paper deals with the problem of calculating the Shapley–Shubik power index in weighted majority games. We propose an efficient Monte Carlo algorithm based on an implicit hierarchical structure of permutations of players.
Yuto Ushioda +2 more
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Convergence of Monte Carlo methods for neutron noise [PDF]
EPJ Web of ConferencesThe neutron noise δφ describes the small variations of the neutron flux around the stationary state φ0, and is typically due to vibrations or oscillations of the core components, induced by fluid-structure interactions and other generally unwanted ...
Fauvel Axel +3 more
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Why Monte Carlo Simulations are Inferences and not Experiments [PDF]
, 2012 Monte Carlo Simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the ...
John D. Norton +3 more
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GENERALIZED SENSITIVITY ANALYSIS CAPABILITY WITH THE DIFFERENTIAL OPERATOR METHOD IN RMC CODE [PDF]
EPJ Web of Conferences, 2021 Sensitivity analysis is an important way for us to know how the input parameters will affect the output of a system. Therefore, recently, there is an increased interest in developing sensitivity analysis methods in continuous-energy Monte Carlo Code due ...
Shi Guanlin +3 more
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Quasi-Monte Carlo simulation of Brownian sheet with application to option pricing
Statistical Theory and Related Fields, 2017 Monte Carlo and quasi-Monte Carlo methods are widely used in scientific studies. As quasi-Monte Carlo simulations have advantage over ordinary Monte Carlo methods, this paper proposes a new quasi-Monte Carlo method to simulate Brownian sheet via its ...
Xinyu Song, Yazhen Wang
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Improved Monte Carlo renormalization group methods [PDF]
, 1984 Hasenfratz A, Hasenfratz P, Heller U, Karsch F. Improved Monte Carlo renormalization group methods. Physics Letters, B. 1984;140(1-2):76-82.The practical application of MCRG requires the flow lines to reach the renormalized trajectory after a small ...
Karsch, Frithjof +6 more
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Química Nova, 2008 The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some fundamental algorithms, concepts and applicability. In order to introduce the quantum Monte Carlo method, preliminary concepts associated with Monte Carlo ...
Wagner Fernando Delfino Angelotti +3 more
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