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On The Comparison Of Several Goodness Of Fit Tests Under Simple Random Sampling And Ranked Set Sampling
release_rev_d6a8b6b6-0fdd-4938-a00b-b74f6c8b43d4
by
F. Azna A. Shahabuddin,
Kamarulzaman Ibrahim,
Abdul Aziz Jemain
Published
by Zenodo.
2009
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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