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Variance and Derivative Estimation of Virtual Performance
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由 Y Lin 著作2018被引用 1 次 — The variance and derivative provide useful information that is not apparent in the mean of virtual performance. Supplementary Material. a17-lin- ...
Variance and derivative estimation for virtual performance in ...
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由 Y Lin 著作2017被引用 1 次 — Virtual statistics are estimators of the virtual performance. In this paper, we go beyond the mean to propose estimators for the variance, and for the ...
(PDF) Variance and Derivative Estimation of Virtual Performance
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The variance and derivative provide useful information that is not apparent in the mean of virtual performance.
variance and derivative estimation for virtual performance in ...
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This paper goes beyond the mean to propose estimators for the variance, and for the derivative of the mean with respect to time, of virtual performance, ...
Variance and derivative estimation for virtual performance in ...
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For more complex random intercept models or for unbalanced data, a simulation study is performed. Most important effects concern estimates and corresponding ...
Variance and derivative estimation for virtual performance in ...
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Yujing Lin, Barry L. Nelson: Variance and derivative estimation for virtual performance in simulation analytics. WSC 2017: 1856-1867. manage site settings.
Variance and derivative estimation of virtual performance
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Virtual statistics are estimators of the virtual performance. In this article, we go beyond the mean to propose estimators for the variance, and for the ...
Yujing Lin
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Variance and derivative estimation for virtual performance in simulation analytics. Y Lin, BL Nelson. Simulation Conference (WSC), 2017 Winter, 1856-1867, ...
Yujing Lin
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Variance and derivative estimation for virtual performance in simulation analytics. Y Lin, BL Nelson. Simulation Conference (WSC), 2017 Winter, 1856-1867, 2017.
Efficient estimation of average derivatives in NPIV models
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由 J Chen 著作2023被引用 10 次 — We present two efficient procedures for estimation and inference on a weighted average derivative (WAD): an orthogonalized plug-in with optimally-weighted ...