Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Marvin K. Nakayama"'
Autor:
Marvin K. Nakayama, Bruno Tuffin
Publikováno v:
2022 Winter Simulation Conference (WSC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d9c59aea59501c0862915d22f7311f80
https://doi.org/10.1109/wsc57314.2022.10015238
https://doi.org/10.1109/wsc57314.2022.10015238
Autor:
Marvin K. Nakayama, Bruno Tuffin
Publikováno v:
Advances in Modeling and Simulation ISBN: 9783031101922
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb6375e691a6958b2fef0d6202c38174
https://doi.org/10.1007/978-3-031-10193-9_17
https://doi.org/10.1007/978-3-031-10193-9_17
Autor:
Marvin K. Nakayama, Bruno Tuffin
Publikováno v:
2021 Winter Simulation Conference (WSC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bff84946ef794fffee053de6e2b8c45d
https://doi.org/10.1109/wsc52266.2021.9715427
https://doi.org/10.1109/wsc52266.2021.9715427
Publikováno v:
WSC
We consider the problem of estimating the p-quantile of a distribution when observations from that distribution are generated from a simulation model. The standard estimator takes the p-quantile of the empirical distribution of independent observatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03c79a3df61a8551385f55bf2c3105e7
https://doi.org/10.1109/wsc48552.2020.9384031
https://doi.org/10.1109/wsc48552.2020.9384031
Publikováno v:
WSC
We consider the estimation of the distribution of the hitting time to a rarely visited set of states for a regenerative process. In a previous paper, we provided two estimators that exploited the weak convergence of the hitting time divided by its ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a873c3257161e75d0e5f1a1223d49953
https://doi.org/10.1109/wsc48552.2020.9383896
https://doi.org/10.1109/wsc48552.2020.9383896
Autor:
Hui Dong, Marvin K. Nakayama
Publikováno v:
Operations Research. 65:1678-1695
Quantiles are often used to measure risk of stochastic systems. We examine quantile estimators obtained using simulation with Latin hypercube sampling (LHS), a variance-reduction technique that efficiently extends stratified sampling to higher dimens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d76558ac7108d49ec347e69429657f65
https://doi.org/10.1287/opre.2017.1637
https://doi.org/10.1287/opre.2017.1637
Publikováno v:
Reliability Engineering & System Safety. 165:376-394
We develop efficient Monte Carlo methods for estimating the failure probability of a system. An example of the problem comes from an approach for probabilistic safety assessment of nuclear power plants known as risk-informed safety-margin characteriz
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3fd45dde5b742659f079ac5cdc1ed183
https://doi.org/10.1016/j.ress.2017.04.001
https://doi.org/10.1016/j.ress.2017.04.001
Publikováno v:
IEEE Transactions on Reliability. 66:258-280
We devise efficient algorithms to construct, evaluate, and approximate a Markovian dependability system with cascading failures. The model, which was previously considered by Iyer et al. , represents a cascading failure as a tree of components that i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::64363ccf7e7f6a95a60ef0f60f979524
https://doi.org/10.1109/tr.2017.2684785
https://doi.org/10.1109/tr.2017.2684785
Autor:
Marvin K. Nakayama, Hui Dong
Publikováno v:
Springer Proceedings in Mathematics & Statistics ISBN: 9783030434649
Quantiles are frequently used to assess risk in a wide spectrum of application areas, such as finance, nuclear engineering, and service industries. This tutorial discusses Monte Carlo simulation methods for estimating a quantile, also known as a perc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b83b779c1535f7010af821011ca7bdd
https://doi.org/10.1007/978-3-030-43465-6_1
https://doi.org/10.1007/978-3-030-43465-6_1
Publikováno v:
WSC 2019-Winter Simulation Conference
WSC 2019-Winter Simulation Conference, Dec 2019, National Harbor, United States. pp.1-14
WSC
WSC 2019-Winter Simulation Conference, Dec 2019, National Harbor, United States. pp.1-14
WSC
International audience; We compare two approaches for quantile estimation via randomized quasi-Monte Carlo (RQMC) in an asymptotic setting where the number of randomizations for RQMC grows large but the size of the low-discrepancy point set remains f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a17a3c18399893dd7bd26e1ae3f04efa
https://inria.hal.science/hal-02155421/file/wsc19-qrqmc-HAL.pdf
https://inria.hal.science/hal-02155421/file/wsc19-qrqmc-HAL.pdf