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Approximating Martingales for Variance Reduction in Markov Process Simulation
Variance reduction Markov process simulation martingale
2015/7/8
“Knowledge of either analytical or numerical approximations should enable more efficient simulation estimators to be constructed.” This principle seems intuitively plausible and certainly attractive, ...
Multifidelity variance reduction for pick-freeze Sobol index estimation
Multifidelity variance reduction pick-freeze Sobol index estimation
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...
American Options Based on Malliavin Calculus and Nonparametric Variance Reduction Methods
American Options Malliavin Calculus Monte Carlo GPU
2011/7/25
Abstract: This paper is devoted to pricing American options using Monte Carlo and the Malliavin calculus. Unlike the majority of articles related to this topic, in this work we will not use localizati...
The excited hadron spectrum in lattice QCD using a new variance reduction method
The excited hadron spectrum lattice QCD
2011/1/7
Progress in calculating the spectrum of excited baryons and mesons in lattice QCD is described. Correlation matrices of sets of spatially-extended hadron operators have been studied and their effectiv...
The excited hadron spectrum in lattice QCD using a new variance reduction method
excited hadron spectrum lattice QCD new variance reduction method
2011/1/14
Progress in calculating the spectrum of excited baryons and mesons in lattice QCD is described.
Correlation matrices of sets of spatially-extended hadron operators have been studied and their
effect...
Design of an Adaptive Particle Filter Based on Variance Reduction Technique
particle filter variance reduction degeneracy
2010/2/23
The main problem of particle filter (PF) in nonlinearstate estimation is the particle degeneracy. Resampling operationsolves degeneracy to some extent, but it results in the problem ofsample impoveris...
Variance reduction in a stochastic volatility scenario
Monte Carlo simulations stochastic di® erential equation variance re-duction stochastic volatility
2009/1/7
This paper investigates the use of a variance reduction, called
importance sampling, for Monte Carlo methods in the case of the stochas-
tic volatility model for option pricing introduced by Hobson ...
Variance reduction for particle filters of systems with time-scale separation
particle filter multiscale dimensional reduction variance reduction Rao-Blackwellization stochastic differential equations jump Markov processes
2010/4/29
We present a particle filter construction for a system
that exhibits time scale separation. The separation of time
scales allows two simplifications that we exploit: i) the use
of the averaging pri...