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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...
Guaranteed Conservative Fixed Width Confidence Intervals Via Monte Carlo Sampling
Guaranteed Conservative Fixed Width Confidence Intervals Monte Carlo Sampling
2012/9/17
Monte Carlo methods are used to approximate the means,? of random variablesY, whose distributions are not known explicitly. The key idea is that the
average of a random sample,Y1,...,Yn, tends to 礱sn...
Fast Parallelized Simulation of 112 Gb/s CP-QPSK Transmission Systems using Stratified Monte-Carlo Sampling
Fiber optics communications Coherent communications
2015/5/26
A novel parallelized implementation of the split-step Fourier method on graphics processing units was developed. The combination of Monte-Carlo simulations with single and double precision yields a sp...
Generalised linear mixed model analysis via sequential Monte Carlo sampling
generalised additive models longitudinal data analysis nonparametric regression sequential Monte Carlo sampler
2009/9/16
We present a sequential Monte Carlo algorithm for the Bayesian analysis of generalised linear mixed models (GLMMs). These models support a variety of interesting regression-type analyses, but performi...
Monte Carlo sampling given a Characteristic Function: Quantile Mechanics in Momentum Space
Monte Carlo Characteristic Function Momentum Space
2010/10/29
In mathematical nance and other applications of stochastic processes, it is frequently the case that the characteristic function may be known but explicit forms for density functions are not availabl...
Efficient Monte Carlo sampling by parallel marginalization
Markov chain Monte Carlo renormalization multi-grid filtering parameterestimation
2010/4/26
Markov chain Monte Carlo sampling methods often suffer from long
correlation times. Consequently, these methods must be run for
many steps to generate an independent sample. In this paper a
method ...