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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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Wednesday, August 9, 2006 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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| Abstract - #305710 |
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Title:
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Estimation for Two-Sample, Location-Scale Models under Type I Censorship
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Author(s):
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Xuewen Lu*+
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Companies:
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University of Calgary
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Address:
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Department of Mathematics and Statistics, Calgary, AB, T2N 1N4, Canada
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Keywords:
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asymptotic normality ; location-scale model ; strong consistency ; type I censorship
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Abstract:
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The author considers a method-of-moments estimation approach to the two-sample, location-scale problem under type I censorship. The estimators for both the location shift and scale change parameters are given. It is shown that the two estimators are strongly consistent, asymptotically normal, and easy to compute. Simulation studies indicate that the proposed estimation procedure performs well in finite samples. A failure-time dataset is used as illustration.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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