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Technometrics Volume 36, 1994 - Issue 1
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Original Articles

Estimation of Extreme Quantiles Based on Sensitivity Tests: A Comparative Study

Linda J. Young Biometry Department, University of Nebraska, Lincoln, NE, 68583-0712
&
Robert G. Easterling Statistics and Human Factors Department, Sandia National Laboratories, Lincoln, Albuquerque, NM, 87185
Pages 48-60 | Published online: 12 Mar 2012

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Jonathan Rougier & Andrew Duncan. (2024) Bayesian Modeling and Inference for One-Shot Experiments. Technometrics 66:1, pages 55-64.
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Brian P. Weaver & Scott A. Vander Wiel. (2023) Accelerated Event Times with Multiple Thresholds. Technometrics 65:4, pages 502-513.
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Edward V. Thomas. (2023) Use of the bias-corrected parametric bootstrap in sensitivity testing/analysis to construct confidence bounds with accurate levels of coverage. Journal of Quality Technology 55:4, pages 442-462.
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Eyal Fisher, Regev Schweiger & Saharon Rosset. (2020) Efficient Construction of Test Inversion Confidence Intervals Using Quantile Regression. Journal of Computational and Graphical Statistics 29:1, pages 140-148.
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Cui Xiong & Jin Xu. (2018) Efficient Robbins–Monro procedure for multivariate binary data. Statistical Theory and Related Fields 2:2, pages 172-180.
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Cui Xiong & Jin Xu. (2016) Confidence Intervals from Stochastic Approximation. Communications in Statistics - Simulation and Computation 45:6, pages 1827-1837.
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BarryT. Never. (1994) A D-Optimality-Based Sensitivity Test. Technometrics 36:1, pages 61-70.
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Articles from other publishers (3)

C.F. Jeff Wu & Yubin Tian. (2014) Rejoinder. Journal of Statistical Planning and Inference 149, pages 30-32.
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C.F. Jeff Wu & Yubin Tian. (2014) Three-phase optimal design of sensitivity experiments. Journal of Statistical Planning and Inference 149, pages 1-15.
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André I. Khuri. 2003. Statistics in Industry. Statistics in Industry 209 229 .

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