Giray Ökten - researchr alias

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Viewing Publication 1 - 25 from 25

2022

Monte Carlo and quasi-Monte Carlo methods for Dempster's rule of combinationNima Salehy, Giray Ökten. ijar, 145:163-186, 2022. [doi]

A Comparison of Global Sensitivity Methods for Power SystemsRuilong Yue, Hui Duan, Giray Ökten, Bahri Uzunoglu. icsrs 2022: 130-137 [doi]

2021

Polynomial Chaos as a Control Variate MethodJamie Fox, Giray Ökten. siamsc, 43(3), 2021. [doi]

Brownian Path Generation and Polynomial ChaosJamie Fox, Giray Ökten. siamfm, 12(2):724-743, 2021. [doi]

Dempster-Shafer Theory for Stock SelectionNima Salehy, Giray Ökten. compsac 2021: 1729-1734 [doi]

Randomized quasi-Monte Carlo methods in global sensitivity analysisGiray Ökten, YaNing Liu. ress, 210:107520, 2021. [doi]

2020

Implementing de-biased estimators using mixed sequencesArun Kumar Polala, Giray Ökten. mcma, 26(4):293-301, 2020. [doi]

2019

Learning shape metrics with Monte Carlo optimizationSerdar Cellat, Yu Fan, Washington Mio, Giray Ökten. jcam, 348:120-129, 2019. [doi]

Global Sensitivity Analysis for Power Systems via Quasi-Monte Carlo MethodsJamie Fox, Giray Ökten, Bahri Uzunoglu. icsrs 2019: 446-451 [doi]

2018

A quasi-Monte Carlo implementation of the ziggurat methodNguyet Nguyen, Linlin Xu, Giray Ökten. mcma, 24(1):93-99, 2018. [doi]

2016

Accurate construction of high dimensional model representation with applications to uncertainty quantificationYaNing Liu, M. Yousuff Hussaini, Giray Ökten. ress, 152:281-295, 2016. [doi]

The acceptance-rejection method for low-discrepancy sequencesNguyet Nguyen, Giray Ökten. mcma, 22(2):133-148, 2016. [doi]

2014

Uncertainty and Robustness in Weather Derivative ModelsAhmet Göncü, YaNing Liu, Giray Ökten, M. Yousuff Hussaini. mcqmc 2016: 351-365 [doi]

Efficient simulation of a multi-factor stochastic volatility modelAhmet Göncü, Giray Ökten. jcam, 259:329-335, 2014. [doi]

Uniform point sets and the collision testAhmet Göncü, Giray Ökten. jcam, 259:798-804, 2014. [doi]

2011

Generating low-discrepancy sequences from the normal distribution: Box-Muller or inverse transform?Giray Ökten, Ahmet Göncü. mcm, 53(5-6):1268-1281, 2011. [doi]

2010

Parameterization based on randomized quasi-Monte Carlo methodsGiray Ökten, Matthew Willyard. pc, 36(7):415-422, 2010. [doi]

2009

Generalized von Neumann-Kakutani transformation and random-start scrambled Halton sequencesGiray Ökten. jc, 25(4):318-331, 2009. [doi]

Correction of a proof in "A probabilistic result on the discrepancy of a hybrid-Monte Carlo sequence and applications"Giray Ökten, Michael Gnewuch. mcma, 15(2):169-172, 2009. [doi]

2008

Parameterization based on randomized quasi-Monte Carlo methodsGiray Ökten, Mathew Willyard. ipps 2008: 1-7 [doi]

On pricing discrete barrier options using conditional expectation and importance sampling Monte CarloGiray Ökten, Emmanuel Salta, Ahmet Göncü. mcm, 47(3-4):484-494, 2008. [doi]

2007

Computation of the endogenous mortgage rates with randomized quasi-Monte Carlo simulationsYevgeny Goncharov, Giray Ökten, Manan Shah. mcm, 46(3-4):459-481, 2007. [doi]

2006

A central limit theorem and improved error bounds for a hybrid-Monte Carlo sequence with applications in computational financeGiray Ökten, Bruno Tuffin, Vadim Burago. jc, 22(4):435-458, 2006. [doi]

2005

Solving Linear Equations by Monte Carlo SimulationGiray Ökten. siamsc, 27(2):511-531, 2005. [doi]

1996

A Probabilistic Result on the Discrepancy of a Hybrid-Monte Carlo Sequence and ApplicationsGiray Ökten. mcma, 2(4):255-270, 1996. [doi]

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