Results 21 to 30 of about 2,281,661 (268)
A HYBRID MONTE-CARLO-DETERMINISTIC METHOD FOR AP1000 EX-CORE DETECTOR RESPONSE SIMULATION [PDF]
EPJ Web of Conferences, 2021 The ex-core detector-response calculation is a typical deep-penetration problem, which is challenging for the Monte Carlo method. The response of the ex-core detector is an important parameter for the safe operation of the nuclear power plants. Meanwhile,
Zheng Qi +6 more
doaj +1 more source
Handbook of Markov Chain Monte Carlo [PDF]
, 2011 Foreword Stephen P. Brooks, Andrew Gelman, Galin L. Jones, and Xiao-Li Meng Introduction to MCMC, Charles J. Geyer A short history of Markov chain Monte Carlo: Subjective recollections from in-complete data, Christian Robert and George Casella Reversible
Radford M. Neal
semanticscholar +1 more source
A general framework for implementing NLO calculations in shower Monte Carlo programs: the POWHEG BOX [PDF]
, 2010 In this work we illustrate the POWHEG BOX, a general computer code framework for implementing NLO calculations in shower Monte Carlo programs according to the POWHEG method.
S. Alioli, P. Nason, C. Oleari, E. Re
semanticscholar +1 more source
, 2006 The structure of events in high-energy collisions is complex and not predictable from first principles. Event generators allow the problem to be subdivided into more manageable pieces, some of which can be described from first principles, while others ...
Sjöstrand, Torbjörn
core +3 more sources
PERHITUNGAN VaR PORTOFOLIO SAHAM MENGGUNAKAN DATA HISTORIS DAN DATA SIMULASI MONTE CARLO
E-Jurnal Matematika, 2012 Value at Risk (VaR) is the maximum potential loss on a portfolio based on the probability at a certain time. In this research, portfolio VaR values calculated from historical data and Monte Carlo simulation data.
WAYAN ARTHINI +2 more
doaj +1 more source
Statistics and Computing, 2021 Motivated mainly by applications to partial differential equations with random coefficients, we introduce a new class of Monte Carlo estimators, called Toeplitz Monte Carlo (TMC) estimator for approximating the integral of a multivariate function with respect to the direct product of an identical univariate probability measure.
Josef Dick, Takashi Goda, Hiroya Murata
openaire +4 more sources
Physics Procedia, 2010 Diagrammatic Monte Carlo (DiagMC) is a numeric technique that allows one to calculate quantities specified in terms of diagrammatic expansions, the latter being a standard tool of many-body quantum statistics. The sign problem that is typically fatal to Monte Carlo approaches, appears to be manageable with DiagMC.
Kris Van Houcke +8 more
openaire +4 more sources
Density Estimation by Monte Carlo and Quasi-Monte Carlo
, 2021 Estimating the density of a continuous random variable X has been studied extensively in statistics, in the setting where n independent observations of X are given a priori and one wishes to estimate the density from that. Popular methods include histograms and kernel density estimators.
L'Ecuyer, P., Puchhammer, F.
openaire +3 more sources
A New Monte Carlo Method for Time-Dependent Neutrino Radiation Transport [PDF]
, 2012 Monte Carlo approaches to radiation transport have several attractive properties compared to deterministic methods. These include simplicity of implementation, high accuracy, and good parallel scaling.
Adam Burrows +51 more
core +2 more sources
Numerical approximation of statistical solutions of scalar conservation laws
, 2014 We propose efficient numerical algorithms for approximating statistical solutions of scalar conservation laws. The proposed algorithms combine finite volume spatio-temporal approximations with Monte Carlo and multi-level Monte Carlo discretizations of ...
Barrett, Paul M. +5 more
core +3 more sources