Results 21 to 30 of about 109,420 (245)
Applied Sciences, 2021 This paper deals with an enhanced robust design optimization (RDO) method and its application to the strength design problem of seat belt anchorage, related to the front crash safety of multi-purpose vehicles.
Chang Yong Song
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A Maximum Entropy Approach to Loss Distribution Analysis
Entropy, 2013 In this paper we propose an approach to the estimation and simulation of loss distributions based on Maximum Entropy (ME), a non-parametric technique that maximizes the Shannon entropy of the data under moment constraints. Special cases of the ME density
Marco Bee
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Robust importance sampling with adaptive winsorization
Bernoulli, 2022 Importance sampling is a widely used technique to estimate properties of a distribution. This paper investigates trading-off some bias for variance by adaptively winsorizing the importance sampling estimator. The novel winsorizing procedure, based on the Balancing Principle (or Lepskii's Method), chooses a threshold level among a pre-defined set by ...
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Qualitative Investigation of Adaptive Divorce: Case Study of Talesh Males During 2014 [PDF]
توسعه اجتماعی, 2018 This study aims to investigate the contexts, conditions, process and consequences of the adaptive divorce in Talesh. 18 males who had adaptively divorced participated at this study.
sorayya pournasiri +2 more
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Adaptive multiple importance sampling for Gaussian processes [PDF]
Journal of Statistical Computation and Simulation, 2017 In applications of Gaussian processes where quantification of uncertainty is a strict requirement, it is necessary to accurately characterize the posterior distribution over Gaussian process covariance parameters. Normally, this is done by means of standard Markov chain Monte Carlo (MCMC) algorithms. Motivated by the issues related to the complexity of
Xiong, Xiaoyu +2 more
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Sensors, 2023 Adaptive information-sampling approaches enable efficient selection of mobile robots’ waypoints through which the accurate sensing and mapping of a physical process, such as the radiation or field intensity, can be obtained.
Aiman Munir, Ramviyas Parasuraman
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Adaptive Importance Sampling for Control and Inference [PDF]
Journal of Statistical Physics, 2016 23 pages, 4 ...
Kappen, H.J., Ruiz, H.C.
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IET Renewable Power Generation, 2021 From the simulation perspective, spinning reserve risk evaluation of power system is commonly a rare‐event assessing issue, for which importance sampling is an appealing solution technique.
Yue Wang
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Adaptive importance sampling in general mixture classes [PDF]
Statistics and Computing, 2008 Removed misleading comment in Section ...
Cappé, Olivier +4 more
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pyLAIS: A Python package for Layered Adaptive Importance Sampling
SoftwareXMonte Carlo (MC) techniques are widely used to draw from complex distributions and/or for the calculation of related integrals. The most famous families of MC methods are Markov Chain Monte Carlo (MCMC) and importance sampling (IS).
Ernesto Curbelo +2 more
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