This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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635
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Type:
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Contributed
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Date/Time:
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Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Computing
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Abstract - #308165 |
Title:
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Finite Sample Properties of Minimum Kolmogorov-Smirnov Estimator and Maximum Likelihood Estimator for Right-Censored Data
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Author(s):
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Jerzy Wieczorek*+ and Jong Sung Kim
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Companies:
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U.S. Census Bureau and Portland State University
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Address:
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, Washington, DC, ,
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Keywords:
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Kolmogorov-Smirnov ;
MLE ;
cdf ;
censoring ;
optimization ;
simulation
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Abstract:
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The MKSFitter algorithm of Weber, Leemis, and Kincaid (2006) computes minimum Kolmogorov-Smirnov estimators (MKSEs) for several continuous univariate distributions, using an evolutionary optimization algorithm, and recommends the distribution and parameter estimates that best minimize the Kolmogorov-Smirnov test statistic. We modify this tool by extending it to use the Kaplan-Meier estimate of the cdf for right-censored data. Using simulated data from the most commonly-used survival distributions, we demonstrate the tool's inability to consistently select the correct distribution type with right-censored data, even for large sample sizes and low censoring rates. We also compare this tool's estimates with the right-censored MLE. While the two estimation techniques have comparable accuracy at low censoring rates, the MKSE significantly underperforms the MLE at higher censoring rates.
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Authors who are presenting talks have a * after their name.
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