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Abstract Details
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Activity Number:
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419
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #306499 |
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Title:
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Approximate Tolerance Limits in a One-Way Random Model Using Bootstrap-Based Higher-Order Asymptotics
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Author(s):
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Elizabeth Murrin*+ and Thomas Mathew
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Companies:
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The Johns Hopkins University Applied Physics Laboratory and University of Maryland Baltimore County
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Address:
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11100 Johns Hopkins Road, Laurel, MD, 20723, United States
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Keywords:
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tolerance limits ;
parametric bootstrap ;
signed roots of likelihood ratios
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Abstract:
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The construction of upper or lower tolerance limits is investigated for a one-way random model with balanced or unbalanced data. It is well known the problem reduces to the computation of an upper or lower confidence limit for a suitable percentile of model. The computation of accurate confidence limits is investigated based on two modified versions of the signed root of the log-likelihood ratio test statistic. The modifications are given in DiCiccio, Martin and Stern (2001,Canadian Journal of Statistics), and are implemented using a parametric bootstrap procedure. The proposed tolerance limits are easy to compute, and numerical results indicate that they are accurate. The results will be illustrated with an example.
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