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Efficient Monte Carlo Simulation of Security Prices
Efficient Monte Carlo Simulation Security Prices
2015/7/8
This paper provides an asymptotically efficient algorithm for the allocation of computing resources to the problem of Monte Carlo integration of continuous-time security prices. The tradeoff between i...
Importance Sampling for Monte Carlo Estimation of Quantiles
quantiles importance sampling large deviations.
2015/7/8
This paper is concerned with applying importance sampling as a variance reduction tool for computing extreme quantiles. A central limit theorem is derived for each of four proposed importance sampling...
Constrained Monte Carlo and the Method of Control Variates
Constrained Monte Carlo Method Control Variates
2015/7/8
A constrained Monte Carlo problem arises when one computes an expectation in the presence of a priori computable constraints on the expectations of quantities that are correlated with the estimand. Th...
A Markov Chain Perspective on Adaptive Monte Carlo Algorithms
Markov Chain Perspective Adaptive Monte Carlo Algorithms
2015/7/8
This paper discusses some connections between adaptive Monte Carlo algorithms and general state space Markov chains. Adaptive algorithms are iterative methods in which previously generated samples are...
Computing the Distribution Function of a Conditional Expectation via Monte Carlo: Discrete Conditioning Spaces
Probability algorithms distribution functions conditional expectation
2015/7/8
We examine different ways of numerically computing the distribution function of conditional expectations where the conditioning element takes values in a finite or countably infinite outcome space. Bo...
How to Deal with the Curse of Dimensionality of Likelihood Ratios in Monte Carlo Simulation
Cross-entropy Rare-event probability estimation Screening Simulation
2015/7/6
In this work we show how to resolve, at least partially, the curse of dimensionality of likelihood ratios (LRs) while using importance sampling (IS) to estimate the performance of high-dimensional Mon...
ERROR ANALYSIS OF COARSE-GRAINED KINETIC MONTE CARLO METHOD
Coarse grain kinetic monte carlo simulation grid the stochastic dynamics structural model
2014/12/25
In this paper we investigate the approximation properties of the coarse-graining procedure applied to kinetic Monte Carlo simulations of lattice stochastic dynamics. We provide both analytical and num...
Coupled coarse graining and Markov Chain Monte Carlo for lattice systems
Markov chain monte carlo random lattice model the short-range particles energy
2014/12/24
We propose an efficient Markov Chain Monte Carlo method for sampling equilibrium distributions for stochastic lattice models, capable of handling correctly long and short-range particle interactions. ...
针对部分可观察马尔可夫决策过程(POMDPs) 的信念状态空间是一个双指数规模问题, 提出一种基于Monte
Carlo 粒子滤波的POMDPs 在线算法. 首先, 分别采用粒子滤波和粒子映射更新和扩展信念状态, 建立可达信念状态
与或树; 然后, 采用分支界限裁剪方法对信念状态与或树进行裁剪, 降低求解规模. 实验结果表明, 所提出算法具有较
低的误差率和较快的收敛性, 能够满足系统实时性...
An Adaptive Sequential Monte Carlo Algorithm for Computing Permanents
Sequential Monte Carlo Permanents Relative Variance
2013/6/14
We consider the computation of the permanent of a binary n by n matrix. It is well- known that the exact computation is a #P complete problem. A variety of Markov chain Monte Carlo (MCMC) computationa...
Bayesian Multi-Dipole Modeling of Single MEG Topographies by Adaptive Sequential Monte Carlo Samplers
Magnetoencephalography inverse problem Multi-object estimation Multi-dipole models Adaptive Sequential Monte Carlo samplers
2013/6/14
We describe a novel Bayesian approach to the estimation of neural currents from a single distribution of magnetic field, measured by magnetoencephalography. We model neural currents as an unknown numb...
Inference in Kingman's Coalescent with Particle Markov Chain Monte Carlo Method
Inference Kingman's Coalescent with Particle Markov Chain Monte Carlo Method
2013/6/13
We propose a new algorithm to do posterior sampling of Kingman's coalescent, based upon the Particle Markov Chain Monte Carlo methodology. Specifically, the algorithm is an instantiation of the Partic...
Statistical inference for Sobol pick freeze Monte Carlo method
Statistical inference Sobol pick freeze Monte Carlo method
2013/4/28
Many mathematical models involve input parameters, which are not precisely known. Global sensitivity analysis aims to identify the parameters whose uncertainty has the largest impact on the variabilit...
Towards Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach
Adaptive Monte Carlo algorithms Bayesian model comparison Normalising constants Path sampling Thermodynamic integration
2013/4/27
Model comparison for the purposes of selection, averaging and validation is a problem found throughout statistics and related disciplines. Within the Bayesian paradigm, these problems all require the ...
Toward Optimal Stratification for Stratified Monte-Carlo Integration
Toward Optimal Stratification Stratified Monte-Carlo Integration
2013/4/27
We consider the problem of adaptive stratified sampling for Monte Carlo integration of a noisy function, given a finite budget n of noisy evaluations to the function. We tackle in this paper the probl...