First Advisor

Jong Sung Kim

Term of Graduation

Spring 2009

Date of Publication

6-2009

Document Type

Paper

Department

Mathematics and Statistics

Language

English

Subjects

Mathematical optimization, Mathematical statistics

DOI

10.15760/etd.7768

Physical Description

1 online resource (12 pages)

Abstract

MKSFitter computes minimum Kolmogorov-Smirnov estimators (MKSEs) for several different continuous univariate distributions, using an evolutionary optimization algorithm, and recommends the distribution and parameter estimates that best minimize the Kolmogorov-Smirnov (K-S) test statistic. We modify this tool by extending it to use the Kaplan-Meier estimate of the cumulative distribution function (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 maximum likelihood estimator (MLE). While the two estimation techniques have comparable accuracy at low censoring rates, the MKSE significantly underperforms the MLE at moderate and severe censoring rates.

Rights

© 2009 Jerzy Wieczorek

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

Comments

This masters project was created for MATH 501/STAT 501 Literature and Problems Research course.

Persistent Identifier

https://archives.pdx.edu/ds/psu/37175

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