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Activity Number:
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355
- Contributed Poster Presentations: Biopharmaceutical Section
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Type:
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Contributed
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Date/Time:
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Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #304856
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Title:
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Bootstrap Calibration for Parametric Tolerance Intervals to Improve Coverage Probabilities
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Author(s):
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Yixuan Zou* and Derek Young
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Companies:
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University of Kentucky and University of Kentucky
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Keywords:
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Weibull Distribution;
Exponential Distribution;
Tolerance Limit
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Abstract:
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Closed-form two-sided parametric tolerance intervals have only been developed for the normal distribution, while closed-form one-sided parametric tolerance limits are available for only a limited number of distributions. Two-sided parametric tolerance intervals which do not have a closed-form solution often use the Bonferroni correction on the one-sided tolerance interval calculation, which incurs a higher coverage probability than the nominal level. A general treatment using bootstrap calibration to improve coverage probability of two-sided parametric tolerance interval to the nominal level is proposed. We present simulation results and analyses of real data for various parametric distributions to show that the coverage probability of the different tolerance intervals when using bootstrap calibration are much closer to nominal levels over those that are uncalibrated.
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Authors who are presenting talks have a * after their name.
