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Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers

Alternative to the least square coefficient of determination ( R2 OLS ), the coefficient of determination based on median absolute deviation,R 2 MAD , is an attractive consideration in the construction of goodness-of-fit test based on regression and correlation, due to its robustness. This st...

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Main Author: Lim, Fong Peng
Format: Thesis
Language:English
English
Published: 2010
Online Access:http://psasir.upm.edu.my/id/eprint/12429/1/FS_2010_11A.pdf
http://psasir.upm.edu.my/id/eprint/12429/
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spelling my.upm.eprints.124292013-05-27T07:52:11Z http://psasir.upm.edu.my/id/eprint/12429/ Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers Lim, Fong Peng Alternative to the least square coefficient of determination ( R2 OLS ), the coefficient of determination based on median absolute deviation,R 2 MAD , is an attractive consideration in the construction of goodness-of-fit test based on regression and correlation, due to its robustness. This study presents the observations made from the resulting plots and descriptive measures obtained from contaminated standard logistic distribution. Contamination is introduced to investigate perseverance of robustness property of R2 MAD for samples from the standard logistic distribution. The sampling distribution of R2 MAD is simulated for various sample sizes (n = 20, 40, 100), percentage of contamination (5%, 15%, 25%) and distribution of the contaminants (logistic (2, 0.2), logistic (0, 0.2), logistic (2, 1) and normal (3, 0.2) contaminants). The symmetricity of the sampling distribution of R2 MAD is observed and followed by the investigation of the confidence intervals of R2 MAD in the presence of outliers. The study of confidence interval estimates for the mean and standard deviation of R2 MAD was conducted using the bootstrap (BCa) method. Tables of critical values for samples from the standard logistic distribution using ZMAD = 1− R2 MAD and ZOLS = 1- R2OLS are constructed. The tables obtained then are used in the power study on the goodness-of-fit tests using test statistic for alternative distributions and contaminated alternative distributions. For lognormal, exponential and standard logistic alternatives, Z*MAD Z and Z *OLS are simulated for various sample sizes (n =10, 20, 30, 50, 100), percentage of contamination (5%, 15%, 25%, 40%) and distribution of the contaminants (logistic (2, 0.2), logistic (0, 0.2), logistic (2, 1) and normal (3, 0.2) contaminants) for different percentiles (a = 0.01, 0.025, 0.05, 0.1), respectively. The results indicated that the test statistic ZMAD is able to discriminate the sample that comes from alternative distributions as the test statistic ZOLS . 2010-03 Thesis NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/12429/1/FS_2010_11A.pdf Lim, Fong Peng (2010) Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers. Masters thesis, Universiti Putra Malaysia. English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Alternative to the least square coefficient of determination ( R2 OLS ), the coefficient of determination based on median absolute deviation,R 2 MAD , is an attractive consideration in the construction of goodness-of-fit test based on regression and correlation, due to its robustness. This study presents the observations made from the resulting plots and descriptive measures obtained from contaminated standard logistic distribution. Contamination is introduced to investigate perseverance of robustness property of R2 MAD for samples from the standard logistic distribution. The sampling distribution of R2 MAD is simulated for various sample sizes (n = 20, 40, 100), percentage of contamination (5%, 15%, 25%) and distribution of the contaminants (logistic (2, 0.2), logistic (0, 0.2), logistic (2, 1) and normal (3, 0.2) contaminants). The symmetricity of the sampling distribution of R2 MAD is observed and followed by the investigation of the confidence intervals of R2 MAD in the presence of outliers. The study of confidence interval estimates for the mean and standard deviation of R2 MAD was conducted using the bootstrap (BCa) method. Tables of critical values for samples from the standard logistic distribution using ZMAD = 1− R2 MAD and ZOLS = 1- R2OLS are constructed. The tables obtained then are used in the power study on the goodness-of-fit tests using test statistic for alternative distributions and contaminated alternative distributions. For lognormal, exponential and standard logistic alternatives, Z*MAD Z and Z *OLS are simulated for various sample sizes (n =10, 20, 30, 50, 100), percentage of contamination (5%, 15%, 25%, 40%) and distribution of the contaminants (logistic (2, 0.2), logistic (0, 0.2), logistic (2, 1) and normal (3, 0.2) contaminants) for different percentiles (a = 0.01, 0.025, 0.05, 0.1), respectively. The results indicated that the test statistic ZMAD is able to discriminate the sample that comes from alternative distributions as the test statistic ZOLS .
format Thesis
author Lim, Fong Peng
spellingShingle Lim, Fong Peng
Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers
author_facet Lim, Fong Peng
author_sort Lim, Fong Peng
title Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers
title_short Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers
title_full Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers
title_fullStr Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers
title_full_unstemmed Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers
title_sort goodness-of-fit test for standard logistics distribution with outliers
publishDate 2010
url http://psasir.upm.edu.my/id/eprint/12429/1/FS_2010_11A.pdf
http://psasir.upm.edu.my/id/eprint/12429/
_version_ 1643825036701728768
score 13.211869

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