This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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38
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #308351 |
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Title:
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A Parametric Bootstrap Procedure for the Generalized Exponential Distribution Under Progressive Type-I Interval Censoring
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Author(s):
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Yuhlong Lio*+ and Din Chen
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Companies:
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The University of South Dakota and Georgia Southern University
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Address:
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414 East Clark Street, Vermillion, SD, 57069,
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Keywords:
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Bias-correction ;
Bootstrapping ;
maximum likelihood estimation ;
Percentiles ;
Progressive type-I interval-censoring
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Abstract:
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A parametric bootstrap procedure is proposed in this paper for the progressively type-I interval censored data from a generalized exponential distribution. The main purpose for this study is to investigate the estimators of the lower confidence bounds on the generalized exponential distribution percentiles based on progressively type-I interval censored data via different corrections. An intensive simulation is conducted to evaluate the estimations of the lower confidence bounds of the generalized exponential distribution percentiles. Finally, the proposed procedures are applied to an illustrative example which contains 112 patients with plasma cell myeloma.
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