This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 635
Type: Contributed
Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #308165
Title: Finite Sample Properties of Minimum Kolmogorov-Smirnov Estimator and Maximum Likelihood Estimator for Right-Censored Data
Author(s): Jerzy Wieczorek*+ and Jong Sung Kim
Companies: U.S. Census Bureau and Portland State University
Address: , Washington, DC, ,
Keywords: Kolmogorov-Smirnov ; MLE ; cdf ; censoring ; optimization ; simulation
Abstract:

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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