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contributor authorوحیده احراری خلفen
contributor authorسیمیندخت براتپورباجگیرانen
contributor authorآرزو حبیبی رادen
contributor authorوحید فکورen
contributor authorvahideh ahrarifa
contributor authorSimindokht Baratpour Bajgiranfa
contributor authorArezou Habibiradfa
contributor authorVahid Fakoorfa
date accessioned2020-06-06T13:46:40Z
date available2020-06-06T13:46:40Z
date issued2019
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/3368628?locale-attribute=en&show=full
description abstractIn the recent studies, much attention has been paid to the usefulness and importance of quantile functions as an alternative approach
in statistical modeling, analysis of data and information theory. In
the present paper, some new divergence measures based on quantile are proposed and then utilizing these divergence measures,
some goodness of fit tests for Rayleigh distribution are constructed.
Monte Carlo simulations are performed for various alternatives and
sample sizes in order to compare the proposed tests with other
goodness of fit tests for Rayleigh distribution in the literature.
Simulation results show that in comparison with the existing tests,
our proposed tests have good performances. Finally, illustrative
examples for use of the proposed tests are presented and analyzed
en
languageEnglish
titleGoodness of fit tests for Rayleigh distribution based on quantilesen
typeJournal Paper
contenttypeExternal Fulltext
subject keywordsGoodness of fit testen
subject keywordsMonte Carlo simulationen
subject keywordsQuantileen
subject keywords
Rayleigh distribution
en
identifier doi10.1080/03610918.2019.1651336
journal titleCommunications in Statistics Part B: Simulation and Computationfa
identifier linkhttps://profdoc.um.ac.ir/paper-abstract-1075753.html
identifier articleid1075753


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