搜索结果: 1-15 共查到“数学 monte carlo”相关记录38条 . 查询时间(0.25 秒)
One-dimensional model of interacting-step fluctuations on vicinal surfaces:Analytical formulas and kinetic Monte Carlo simulations
One-dimensional model interacting-step fluctuations vicinal surfaces Analytical formulas kinetic Monte Carlo simulations
2015/10/16
We study analytically and numerically a one-dimensional model of interacting line defects steps fluctuating on a vicinal crystal. Our goal is to formulate and validate analytical techniques for appr...
CONNECTION OF KINETIC MONTE CARLO MODEL FOR SURFACES TO ONE-STEP FLOW THEORY IN 1+1 DIMENSIONS
kinetic Monte Carlo Burton–Cabrera–Frank theory low-density approximation near-equilibrium condition master equation maximum principle
2015/10/16
The Burton–Cabrera–Frank (BCF) theory of step flow has been recognized as a valuable tool for describing nanoscale evolution of crystal surfaces. We formally derive a single-step BCF-type model from a...
Discussion of: \Sequential Quasi-Monte-Carlo Sampling" by Mathieu Gerber and Nicolas Chopin
Mathieu Gerber Nicolas Chopin
2015/8/21
We congratulate Gerber and Chopin for a very interesting paper with much
promise for applications. SQMC is similar to array-RQMC (L'Ecuyer et al.,
2008), in using T sets of N points in [0;1]d
inste...
Guaranteed Conservative Fixed Width Confidence Intervals Via Monte Carlo Sampling
Intervals Via Monte Carlo Sampling Guaranteed Conservative
2015/8/21
Monte Carlo methods are used to approximate the means, μ, of random variables
Y, whose distributions are not known explicitly. The key idea is that the average of a random
sample, Y1,...,Yn, tends t...
MONTE CARLO SAMPLING IN DUAL SPACE FOR APPROXIMATING THE EMPIRICAL HALFSPACE DISTANCE
SPACE FOR APPROXIMATING EMPIRICAL HALFSPACE DISTANCE
2015/8/20
The Kolmogorov]Smirnov distance is an important tool for constructing confidence sets and tests in univariate problems. In multivariate
settings, an analogous role is played by the halfspace di...
THREE EXAMPLES OF MONTE-CARLO MARKOV CHAINS:AT THE INTERFACE BETWEEN STATOSTICAL COMPUTING,COMPUTER SCIENCE,AND STATISTICAL MECHANICS
Monte carlo markov chain the interface between computing computer science statistical mechanics
2015/7/14
THREE EXAMPLES OF MONTE-CARLO MARKOV CHAINS:AT THE INTERFACE BETWEEN STATOSTICAL COMPUTING,COMPUTER SCIENCE,AND STATISTICAL MECHANICS。
Sequential Monte Carlo Methods for Statistical Analysis of Tables
Conditional inference Contingency table Counting problem Exact test Sequential importance sampling Zero–one table
2015/7/8
Sequential Monte Carlo Methods for Statistical Analysis of Tables.
The Markov Chain Monte Carlo Revolution。
Some things we’ve learned (about Markov chain Monte Carlo)
Markov chains nonreversible chains rates of convergence
2015/7/7
This paper offers a personal review of some things we’ve learned about rates of convergence of Markov chains to their stationary distributions. The main topic is ways of speeding up diffusive behavior...
de Finetti Priors using Markov chain Monte Carlo computations
Priors MCMC Contingency Tables Bayesian Inference Independence
2015/7/7
de Finetti Priors using Markov chain Monte Carlo computations。
Quasi Monte Carlo Simulation of Stochastic String Model
Quasi Monte Carlo Simulation Stochastic String Model
2015/3/20
Quasi Monte Carlo Simulation of Stochastic String Model.
Rao-Blackwellised Interacting Markov Chain Monte Carlo for Electromagnetic Scattering Inversion
Rao-Blackwellised Markov Chain Monte Carlo Electromagnetic Scattering Inversion
2012/11/22
The following electromagnetism (EM) inverse problem is addressed. It consists in estimating local radioelectric properties of materials recovering an object from the global EM scattering measurement, ...
On nonlinear Markov chain Monte Carlo
Foster–Lyapunov condition interacting Markov chains nonlinear Markov kernels Poisson equation
2011/9/9
Abstract: Let $\mathscr{P}(E)$ be the space of probability measures on a measurable space $(E,\mathcal{E})$. In this paper we introduce a class of nonlinear Markov chain Monte Carlo (MCMC) methods for...
A global Monte-Carlo method for fitting parameters of differential equation models
global Monte-Carlo method fitting parameters Quantitative Methods
2011/10/8
Abstract: Finding the parameter values of differential equation models from data is an important part of the modelling process. Large models and sparse data often make the parameters very difficult to...
Multi-level Monte Carlo for stochastically modeled chemical kinetic systems
computational complexity diffusion Gillespie Langevin next reaction method random time change tau-leaping variance
2011/9/1
Abstract: A chemical reaction network involves multiple reactions and species. The simplest stochastic models of such networks treat the system as a continuous time Markov chain with the state being t...