Results 31 to 40 of about 708,503 (346)

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, Masato Tanaka, Tomomi Matsui   +2 more
doaj   +1 more source

Semistochastic Projector Monte Carlo Method

Physical Review Letters, 2012
We introduce a semistochastic implementation of the power method to compute, for very large matrices, the dominant eigenvalue and expectation values involving the corresponding eigenvector. The method is semistochastic in that the matrix multiplication is partially implemented numerically exactly and partially with respect to expectation values only ...
Petruzielo, F. R., Holmes, A. A., Changlani, Hitesh J., Nightingale, M. P., Umrigar, C. J.   +4 more
openaire   +5 more sources

Riemann manifold Langevin and Hamiltonian Monte Carlo methods

Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2011
Summary.  The paper proposes Metropolis adjusted Langevin and Hamiltonian Monte Carlo sampling methods defined on the Riemann manifold to resolve the shortcomings of existing Monte Carlo algorithms when sampling from target densities that may be high ...
M. Girolami, B. Calderhead
semanticscholar   +1 more source

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
doaj   +1 more source

Uma abordagem simplificada do método Monte Carlo Quântico: da solução de integrais ao problema da distribuição eletrônica A simplified approach to the Quantum Monte Carlo method: from the solution of integrals to the electronic distribution problem

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, André Luiz da Fonseca, Guilherme Barreto Torres, Rogério Custodio   +3 more
doaj   +1 more source

Markov Chain Monte Carlo Solution of Poisson’s Equation in Axisymmetric Regions

Advanced Electromagnetics, 2019
The advent of the Monte Carlo methods to the field of EM have seen floating random walk, fixed random walk and Exodus methods deployed to solve Poisson’s equation in rectangular coordinate and axisymmetric solution regions.
A. E. Shadare, M. N. O. Sadiku, S. M. Musa   +2 more
doaj   +1 more source

Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions

Entropy, 2014
Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo
Samuel Livingstone, Mark Girolami
doaj   +1 more source

The Convergence of Markov Chain Monte Carlo Methods: From the Metropolis Method to Hamiltonian Monte Carlo [PDF]

, 2017
From its inception in the 1950s to the modern frontiers of applied statistics, Markov chain Monte Carlo has been one of the most ubiquitous and successful methods in statistical computing. The development of the method in that time has been fueled by not
M. Betancourt
semanticscholar   +1 more source

Quasi-Monte Carlo and Multilevel Monte Carlo Methods for Computing Posterior Expectations in Elliptic Inverse Problems [PDF]

SIAM/ASA J. Uncertain. Quantification, 2016
We are interested in computing the expectation of a functional of a PDE solution under a Bayesian posterior distribution. Using Bayes's rule, we reduce the problem to estimating the ratio of two related prior expectations.
Robert Scheichl, A. Stuart, A. Teckentrup   +2 more
semanticscholar   +1 more source

Optimized monte carlo methods [PDF]

, 2008
I discuss optimized data analysis and Monte Carlo methods. Reweighting methods are discussed through examples, like Lee-Yang zeroes in the Ising model and the absence of deconfinement in QCD. I discuss reweighted data analysis and multi-hystogramming. I introduce Simulated Tempering, and as an example its application to the Random Field Ising Model.
openaire   +2 more sources