Adaptive importance sampling for extreme quantile estimation with stochastic black box computer models

Naval Research Logistics (NRL) ◽

10.1002/nav.21938 ◽

2020 ◽

Vol 67 (7) ◽

pp. 524-547

Author(s):

Qiyun Pan ◽

Eunshin Byon ◽

Young Myoung Ko ◽

Henry Lam

Keyword(s):

Importance Sampling ◽

Computer Models ◽

Black Box ◽

Quantile Estimation ◽

Adaptive Importance Sampling ◽

Extreme Quantile

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Extreme quantile estimation with nonparametric adaptive importance sampling

Simulation Modelling Practice and Theory ◽

10.1016/j.simpat.2012.05.008 ◽

2012 ◽

Vol 27 ◽

pp. 76-89 ◽

Author(s):

Jérôme Morio

Keyword(s):

Importance Sampling ◽

Quantile Estimation ◽

Adaptive Importance Sampling ◽

Extreme Quantile

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Quantile Estimation with Adaptive Importance Sampling

SSRN Electronic Journal ◽

10.2139/ssrn.1002631 ◽

2007 ◽

Author(s):

Daniel Egloff ◽

Markus Leippold

Keyword(s):

Importance Sampling ◽

Quantile Estimation ◽

Adaptive Importance Sampling

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Quantile estimation with adaptive importance sampling

The Annals of Statistics ◽

10.1214/09-aos745 ◽

2010 ◽

Vol 38 (2) ◽

pp. 1244-1278 ◽

Author(s):

Daniel Egloff ◽

Markus Leippold

Keyword(s):

Importance Sampling ◽

Quantile Estimation ◽

Adaptive Importance Sampling

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Uncertainty Quantification for Extreme Quantile Estimation With Stochastic Computer Models

IEEE Transactions on Reliability ◽

10.1109/tr.2020.2980448 ◽

2020 ◽

pp. 1-12 ◽

Author(s):

Qiyun Pan ◽

Young Myoung Ko ◽

Eunshin Byon

Keyword(s):

Uncertainty Quantification ◽

Computer Models ◽

Quantile Estimation ◽

Extreme Quantile

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Adaptive Importance Sampling Via Auto-Regressive Generative Models and Gaussian Processes

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp39728.2021.9414734 ◽

2021 ◽

Author(s):

Hechuan Wang ◽

Monica F. Bugallo ◽

Petar M. Djuric

Keyword(s):

Importance Sampling ◽

Gaussian Processes ◽

Generative Models ◽

Adaptive Importance Sampling ◽

Auto Regressive

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Time-variant nonparametric extreme quantile estimation with application to US temperature data

South African Statistical Journal ◽

10.37920/sasj.2021.55.2.1 ◽

2021 ◽

Vol 55 (2) ◽

pp. 87-108

Author(s):

Mohammed Chowdhury ◽

Bogdan Gadidov ◽

Linh Le ◽

Yan Wang ◽

Lewis VanBrackle

Keyword(s):

Temperature Data ◽

Quantile Estimation ◽

Extreme Quantile

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Extreme quantile estimation for dependent data, with applications to finance

Bernoulli ◽

10.3150/bj/1066223272 ◽

2003 ◽

Vol 9 (4) ◽

pp. 617-657 ◽

Author(s):

Holger Drees

Keyword(s):

Quantile Estimation ◽

Dependent Data ◽

Extreme Quantile

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Application of crude Monte Carlo and adaptive importance sampling in reliability assessment of URM shear walls

Brick and Block Masonry ◽

10.1201/b21889-39 ◽

2016 ◽

pp. 331-338

Author(s):

H. Salehi ◽

M. Montazerolghaem ◽

W. Jäger

Keyword(s):

Monte Carlo ◽

Importance Sampling ◽

Reliability Assessment ◽

Shear Walls ◽

Adaptive Importance Sampling

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Extreme quantile estimation forβ-mixing time series and applications

Insurance Mathematics and Economics ◽

10.1016/j.insmatheco.2018.09.004 ◽

2018 ◽

Vol 83 ◽

pp. 59-74

Author(s):

Valérie Chavez-Demoulin ◽

Armelle Guillou

Keyword(s):

Time Series ◽

Mixing Time ◽

Quantile Estimation ◽

Extreme Quantile

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Adaptive Importance Sampling Algorithms for Transport Problems

Monte-Carlo and Quasi-Monte Carlo Methods 1998 ◽

10.1007/978-3-642-59657-5_18 ◽

2000 ◽

pp. 273-283 ◽

Author(s):

Yongzeng Lai ◽

Jerome Spanier

Keyword(s):

Importance Sampling ◽

Adaptive Importance Sampling ◽

Sampling Algorithms ◽

Transport Problems

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