Results 61 to 70 of about 545,959 (267)
Multilevel Monte Carlo for exponential Lévy models [PDF]
Finance and Stochastics, 2017 We apply multilevel Monte Carlo for option pricing problems using exponential L vy models with a uniform timestep discretisation to monitor the running maximum required for lookback and barrier options. The numerical results demonstrate the computational efficiency of this approach.
Mike Giles, Yuan Xia
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AppliedMath, 2023 A multilevel Monte Carlo (MLMC) method is applied to simulate a stochastic optimal problem based on the gradient projection method. In the numerical simulation of the stochastic optimal control problem, the approximation of expected value is involved ...
Changlun Ye, Xianbing Luo
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Simultaneous detection of gradual and abrupt structural changes in Bayesian longitudinal modelling using entropy and model fit measures. [PDF]
Br J Math Stat PsycholAbstract Although individuals may exhibit both gradual and abrupt changes in their dynamic properties as shaped by both slowly accumulating influences and acute events, existing statistical frameworks offer limited capacity for the simultaneous detection and representation of these distinct change patterns.
Li Y, Xiong X, Oravecz Z, Chow SM.
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Multilevel Mixture Kalman Filter
EURASIP Journal on Advances in Signal Processing, 2004 The mixture Kalman filter is a general sequential Monte Carlo technique for conditional linear dynamic systems. It generates samples of some indicator variables recursively based on sequential importance sampling (SIS) and integrates out the linear and ...
Xiaodong Wang, Dong Guo, Rong Chen
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Unbiased Estimators and Multilevel Monte Carlo [PDF]
Operations Research, 2018 Multilevel Monte Carlo (MLMC) and recently proposed unbiased estimators are closely related. This connection is elaborated by presenting a new general class of unbiased estimators, which admits previous debiasing schemes as special cases. New lower variance estimators are proposed, which are stratified versions of earlier unbiased schemes.
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Applied Sciences, 2022 Groundwater contaminant transport modeling is a vitally important topic. Since modeled processes include uncertainties, Monte Carlo methods are adopted to obtain some statistics. However, accurate models have a substantial computational cost.
Martin Špetlík, Jan Březina
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, 2013 The Euler-Maruyama scheme is known to diverge strongly and numerically weakly when applied to nonlinear stochastic differential equations (SDEs) with superlinearly growing and globally one-sided Lipschitz continuous drift coefficients.
Hutzenthaler, Martin +2 more
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ESAIM: Proceedings and Surveys, 2017 In this paper, we recall the result about the strong convergence rate of the Ninomiya-Victoir scheme and the properties of the multilevel Monte Carlo estimators involving this scheme that we introduced and studied in [2].
Al Gerbi A., Jourdain B., Clément E.
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Multilevel Monte Carlo methods for ensemble variational data assimilation [PDF]
Nonlinear Processes in GeophysicsEnsemble variational data assimilation relies on ensembles of forecasts to estimate the background error covariance matrix B. The ensemble can be provided by an ensemble of data assimilations (EDA), which runs independent perturbed data assimilation and ...
M. Destouches +10 more
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Sleep Reactivity Amplifies the Impact of Pre-Sleep Cognitive Arousal on Sleep Disturbances. [PDF]
J Sleep ResThis study investigates how sleep reactivity moderates the ‘stress‐pre‐sleep arousal‐sleep’ pathway in university students. At the within‐individual level, both high and low sleep‐reactive groups showed increased pre‐sleep cognitive arousal and sleep disruptions in response to elevated daily stress.
Shaif NAS +5 more
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