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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主要作者: Lim, Fong Peng
格式: Thesis
语言:English
English
出版: 2010
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spelling my-upm-ir.124292013-05-27T07:52:11Z Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers 2010-03 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 . Outliers (Statistics) Logistic distribution 2010-03 Thesis http://psasir.upm.edu.my/id/eprint/12429/ http://psasir.upm.edu.my/id/eprint/12429/1/FS_2010_11A.pdf application/pdf en public masters Universiti Putra Malaysia Outliers (Statistics) Logistic distribution Faculty Of Science English
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
English
topic Outliers (Statistics)
Logistic distribution

spellingShingle Outliers (Statistics)
Logistic distribution

Lim, Fong Peng
Goodness-Of-Fit Test For Standard Logistics Distribution With Outliers
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
qualification_level Master's degree
author Lim, Fong Peng
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
granting_institution Universiti Putra Malaysia
granting_department Faculty Of Science
publishDate 2010
url http://psasir.upm.edu.my/id/eprint/12429/1/FS_2010_11A.pdf
_version_ 1747811364230922240