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Journal of the American Statistical Association, 1949
Abstract In this paper Metropolis and Ulam gave a brief introduction to “the Monte Carlo method” which is described as a statistical approach to the study of differential equations as applied by Metropolis, Ulam, Fermi, von Neumann, Feynman, and others at the Los Alamos Laboratory in the 1940s.0 Several examples of applications of Monte ...
N, METROPOLIS, S, ULAM
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Abstract In this paper Metropolis and Ulam gave a brief introduction to “the Monte Carlo method” which is described as a statistical approach to the study of differential equations as applied by Metropolis, Ulam, Fermi, von Neumann, Feynman, and others at the Los Alamos Laboratory in the 1940s.0 Several examples of applications of Monte ...
N, METROPOLIS, S, ULAM
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Monte Carlo and Quasi-Monte Carlo Methods
2020Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N~1^2), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction ...
Tuffin, Bruno, L'Écuyer, Pierre
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2019
The sequential use of random numbers, to sample the values of probability variables, allows obtaining solutions to mathematical problems such as the Monte Carlo method, that allows to model stochastic parameters or deterministic based on random sampling.
Lorenzo Cevallos-Torres +1 more
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The sequential use of random numbers, to sample the values of probability variables, allows obtaining solutions to mathematical problems such as the Monte Carlo method, that allows to model stochastic parameters or deterministic based on random sampling.
Lorenzo Cevallos-Torres +1 more
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1987
The term ‘Monte Carlo methods’ is used to refer to two different, though closely related, techniques. The first meaning, currently the less common one among economists, is the evaluation of definite integrals by use of random variables. The idea is to evaluate \(\int_a^b {F\left( x \right)} {\text{d}}x\) where x may be a vector) by estimating \(\int_a ...
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The term ‘Monte Carlo methods’ is used to refer to two different, though closely related, techniques. The first meaning, currently the less common one among economists, is the evaluation of definite integrals by use of random variables. The idea is to evaluate \(\int_a^b {F\left( x \right)} {\text{d}}x\) where x may be a vector) by estimating \(\int_a ...
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Journal of the Society for Industrial and Applied Mathematics, 1958
A description of the many facets of the Monte Carlo Method is presented. The subject is traversed from the most elementary to the more difficult techniques, and from the least practical to the most fruitful applications. The generation of random numbers in the modern electronic computing machine is dealt with.
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A description of the many facets of the Monte Carlo Method is presented. The subject is traversed from the most elementary to the more difficult techniques, and from the least practical to the most fruitful applications. The generation of random numbers in the modern electronic computing machine is dealt with.
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Monte Carlo and Quasi-Monte Carlo Methods
2013Chapter 12 discusses Monte Carlo and quasi-Monte Carlo methods and demonstrates how these techniques can be used to compute functionals of multidimensional diffusions. Monte Carlo methods feature prominently in this book, in particular we discuss how to use Lie Symmetry methods to construct unbiased Monte Carlo estimators in Chap. 6, and we discuss how
Jan Baldeaux, Eckhard Platen
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Monte Carlo and quasi-Monte Carlo methods
Acta Numerica, 1998Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N−1/2), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction ...
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2018
Stochastic-simulation, or Monte-Carlo, methods are used extensively in the area of credit-risk modelling. This technique has, in fact, been employed inveterately in previous chapters. Care and caution are always advisable when employing a complex numerical technique. Prudence is particularly appropriate, in this context, because default is a rare event.
Philip Dutré +2 more
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Stochastic-simulation, or Monte-Carlo, methods are used extensively in the area of credit-risk modelling. This technique has, in fact, been employed inveterately in previous chapters. Care and caution are always advisable when employing a complex numerical technique. Prudence is particularly appropriate, in this context, because default is a rare event.
Philip Dutré +2 more
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2000
The written history of the Monte Carlo methods began in 1949 after the paper of Metropolis and Ulm [1949], but at that time the method had already been used for several years in secret defense projects of the United States of America for simulating the behaviour of nuclear reactors. It was definitely known to J. Von Neumann, N. Metropolis, S.M. Ulm, H.
Helmut Neunzert, Abul Hasan Siddiqi
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The written history of the Monte Carlo methods began in 1949 after the paper of Metropolis and Ulm [1949], but at that time the method had already been used for several years in secret defense projects of the United States of America for simulating the behaviour of nuclear reactors. It was definitely known to J. Von Neumann, N. Metropolis, S.M. Ulm, H.
Helmut Neunzert, Abul Hasan Siddiqi
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2009
Monte Carlo methods comprise a large and still growing collection of methods of repetitive simulation designed to obtain approximate solutions of various problems by playing games of chance. Often these methods are motivated by randomness inherent in the problem being studied (as, e.g., when simulating the random walks of “particles” undergoing ...
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Monte Carlo methods comprise a large and still growing collection of methods of repetitive simulation designed to obtain approximate solutions of various problems by playing games of chance. Often these methods are motivated by randomness inherent in the problem being studied (as, e.g., when simulating the random walks of “particles” undergoing ...
openaire +1 more source