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On the variance of single-run unbiased stochastic derivative estimators
Cui, Zhenyu; Fu, Michael; Hu, Jian-Qiang; Liu, Yanchu; … - In: INFORMS journal on computing : JOC 32 (2020) 2, pp. 390-407
Persistent link: https://www.econbiz.de/10012242769
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A new unbiased stochastic derivative estimator for discontinuous sample performances with structural parameters
Peng, Yijie; Fu, Michael; Hu, Jian-Qiang; Heidergott, Bernd - In: Operations research 66 (2018) 2, pp. 487-499
Persistent link: https://www.econbiz.de/10011845997
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Maximum likelihood estimation by Monte Carlo simulation : toward data-driven stochastic modeling
Peng, Yijie; Fu, Michael; Heidergott, Bernd; Lam, Henry - In: Operations research 68 (2020) 6, pp. 1896-1912
Persistent link: https://www.econbiz.de/10012392175
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On estimating quantile sensitivities via infinitesimal perturbation analysis
Jiang, Guangxin; Fu, Michael - In: Operations research 63 (2015) 2, pp. 435-441
Persistent link: https://www.econbiz.de/10010526698
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Regression models augmented with direct stochastic gradient estimators
Fu, Michael; Qu, Huashuai - In: INFORMS journal on computing : JOC 26 (2014) 3, pp. 484-499
Persistent link: https://www.econbiz.de/10010399808
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Technical note: central limit theorems for estimated functions at estimated points
Glynn, Peter W.; Fan, Lin; Fu, Michael; Hu, Jian-Qiang; … - In: Operations research 68 (2020) 5, pp. 1557-1563
Persistent link: https://www.econbiz.de/10012301573
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Optimal unbiased estimation for expected cumulative discounted cost
Cui, Zhenyu; Fu, Michael; Peng, Yijie; Zhu, Lingjiong - In: European journal of operational research : EJOR 286 (2020) 2, pp. 604-618
Persistent link: https://www.econbiz.de/10012291551