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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
openaire +2 more sources
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
openaire +2 more sources
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
openaire +1 more source
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
openaire +1 more source
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 ...
openaire +1 more source
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
2006
Abstract Starting with this chapter, we embark on a journey into the fascinating realms of statistical mechanics and computational physics. We set out to study a host of classical and quantum problems, all of value as models and with numerous applications and generalizations.
openaire +1 more source
Abstract Starting with this chapter, we embark on a journey into the fascinating realms of statistical mechanics and computational physics. We set out to study a host of classical and quantum problems, all of value as models and with numerous applications and generalizations.
openaire +1 more source
Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey
Wiley Interdisciplinary Reviews: Computational Statistics, 2021Jiaxin Zhang
exaly
Monte Carlo methods in geophysical inverse problems
Reviews of Geophysics, 2002Malcolm Sambridge, Klaus Mosegaard
exaly
Noncovalent Interactions by Quantum Monte Carlo
Chemical Reviews, 2016Lubos Mitas, Petr Jurečka
exaly