(atechnique in which a large quantity of randomly generated numbers are studiedusing a probabilistic model to find an approximate solution to a numericalproblem that would be difficult to solve by other methods.)那篇wiki的第一句话就是:Not to be confused withMonte Carlo algorithm.详情看Monte Carlo...
randomized algorithmdouble randomization methodrandom mediumsplitting methodstatistical kernel estimatorRandomized Monte Carlo algorithms are constructed by a combination of a basic probabilistic model and its random parameters to investigate parametric distributions of linear functionals. An optimization of the ...
The method for sampling the actions is the key feature of the Monte-Carlo planning. Comparing to the traditional uniformed and randomized sampling methods, the multi-armed bandit algorithm has advantages in balancing the trade-offs between explorations and exploitations during the planning process, and...
This paper studies a new randomized quasi-Monte Carlo method for estimating the mean and variance of the Pareto distribution. In many Monte Carlo simulations, there are some stability problems for estimating the population Pareto variance by using the sample variance. In this paper, we propose a ...
Based on the three-dimensional ELSHOW algorithm, samples of states of particles in an electron avalanche are obtained for a given time moment in order to calculate the corresponding 'diffusion radii' and diffusion coefficients. Randomized projection estimators and kernel estimators (for test purpose) ...
This paper considers the problem of scaling the proposal distribution of a multidimensional random walk Metropolis algorithm in order to maximize the effic... GO Roberts,A Gelman,WR Gilks - 《Annals of Applied Probability》 被引量: 1918发表: 1997年 Accelerating Markov Chain Monte Carlo Simulation...
weproposeanewmethodforstimulusgenerationbasedonMarkovchainMonteCarlo(MCMC)methods.WedescribethebasicprinciplesofMCMCmethodsandoneofthemostcommonofthesemethods,Metropolis-Hastingssampling.Wepresentourapproach,whichcombinestheMetropolis-Hastingsalgorithmwithstochasticlocalsearch.Weshowwithexperimentalresultsthatitsurpasses...
This book represents the refereed proceedings of the Seventh International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, held in Ulm (Germany) in August 2006. The proceedings include carefully selected papers on many aspects of Monte Carlo and quasi-Monte Carlo meth...
Summary: We study the classical Monte Carlo algorithm for weighted multivariate integration. It is well known that if Monte Carlo uses $n$ randomized sample points for a function of $d$ variables then it has error $(ext{var}_d (f)/n)^{1/2}$, where $ext{var}_d(f)$ is the varian...
A randomized quasi-Monte Carlo simulation method for Markov chains The general idea is to obtain a better approximation of the state distribution, at each step of the chain, than with standard Monte Carlo. The ... P L'Ecuyer,Lecot, C,Tuffin, B - 《Operations Research the Journal of the ...