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Activity Number:
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38
- Reliability Insights
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Type:
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Contributed
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Date/Time:
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Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
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Sponsor:
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Quality and Productivity Section
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Abstract #323577
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View Presentation
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Title:
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A General Algorithm for Computing Simultaneous Prediction Intervals for the (Log)-Location-Scale Family of Distributions
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Author(s):
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William Meeker* and Yimeng Xie and Yili Hong and Luis A Escobar
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Companies:
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Iowa State University and Virginia Tech and Virginia Tech and Louisiana State University
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Keywords:
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Censored Data ;
Coverage Probability ;
Lognormal ;
Simulation ;
Weibull
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Abstract:
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Making predictions of future realized values of random variables based on currently available data is a frequently needed task in statistical applications. In some applications, the interest is to obtain a two-sided simultaneous prediction interval (SPI) to contain at least k out of m future observations with a certain confidence level based on n previous observations from the same distribution. A closely related problem is to obtain a one-sided upper (or lower) simultaneous prediction bound (SPB) to exceed (or be exceeded) by at least k out of m future observations. In this paper, we provide a general approach for computing SPIs and SPBs based on data from a particular member of the (log)-location-scale family of distributions with complete or right censored data. The proposed simulation-based procedure can provide exact coverage probability for complete and Type II censored data. For Type I censored data, our simulation results show that our procedure provides satisfactory results in small samples. We use several applications to illustrate the proposed simultaneous prediction intervals and bounds.
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Authors who are presenting talks have a * after their name.
