{"title":"On the Comparison of Several Goodness of Fit tests under Simple Random Sampling and Ranked Set Sampling","authors":"F. A. Shahabuddin, K. Ibrahim, A. Jemain","doi":"10.5281/ZENODO.1072455","DOIUrl":null,"url":null,"abstract":"Many works have been carried out to compare the\nefficiency of several goodness of fit procedures for identifying\nwhether or not a particular distribution could adequately explain a\ndata set. In this paper a study is conducted to investigate the power\nof several goodness of fit tests such as Kolmogorov Smirnov (KS),\nAnderson-Darling(AD), Cramer- von- Mises (CV) and a proposed\nmodification of Kolmogorov-Smirnov goodness of fit test which\nincorporates a variance stabilizing transformation (FKS). The\nperformances of these selected tests are studied under simple\nrandom sampling (SRS) and Ranked Set Sampling (RSS). This\nstudy shows that, in general, the Anderson-Darling (AD) test\nperforms better than other GOF tests. However, there are some\ncases where the proposed test can perform as equally good as the\nAD test.","PeriodicalId":23764,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering","volume":"9 1","pages":"406-409"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Academy of Science, Engineering and Technology, International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5281/ZENODO.1072455","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Many works have been carried out to compare the
efficiency of several goodness of fit procedures for identifying
whether or not a particular distribution could adequately explain a
data set. In this paper a study is conducted to investigate the power
of several goodness of fit tests such as Kolmogorov Smirnov (KS),
Anderson-Darling(AD), Cramer- von- Mises (CV) and a proposed
modification of Kolmogorov-Smirnov goodness of fit test which
incorporates a variance stabilizing transformation (FKS). The
performances of these selected tests are studied under simple
random sampling (SRS) and Ranked Set Sampling (RSS). This
study shows that, in general, the Anderson-Darling (AD) test
performs better than other GOF tests. However, there are some
cases where the proposed test can perform as equally good as the
AD test.
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