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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.
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...
Stable marriage problem under Monte Carlo simulations, influence of preferrence corelation on relaxation time
Stable marriage problem Monte Carlo simulations influence of preferrence corelation relaxation time
2011/7/5
In this paper we consider stable marriage problem under the Monte Carlo
simulations. We investigate how correlation in lists of preferrences can affect
simulation results such as: relaxation time, t...
Sequential Monte Carlo (SMC) methods are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. We propose a new SMC algorithm to compute the expectation...
EM算法是近年来常用的求后验众数的估计的一种数据增广算法, 但由于求出其E步中积分的显示表达式有时很困难, 甚至不可能, 限制了其应用的广泛性. 而Monte Carlo EM算法很好地解决了这个问题, 将EM算法中E步的积分用Monte Carlo模拟来有效实现, 使其适用性大大增强. 但无论是EM算法, 还是Monte Carlo EM算法, 其收敛速度都是线性的, 被缺损信息的倒数所控制, ...