Goodness of fit tests for Rayleigh distribution based on quantiles
Author:
, , , , , , ,Year
: 2019
Abstract: In 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
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
DOI: 10.1080/03610918.2019.1651336
Keyword(s): Goodness of fit test,Monte Carlo simulation,Quantile,
Rayleigh distribution
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Goodness of fit tests for Rayleigh distribution based on quantiles
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| contributor author | وحیده احراری خلف | en |
| contributor author | سیمیندخت براتپورباجگیران | en |
| contributor author | آرزو حبیبی راد | en |
| contributor author | وحید فکور | en |
| contributor author | vahideh ahrari | fa |
| contributor author | Simindokht Baratpour Bajgiran | fa |
| contributor author | Arezou Habibirad | fa |
| contributor author | Vahid Fakoor | fa |
| date accessioned | 2020-06-06T13:46:40Z | |
| date available | 2020-06-06T13:46:40Z | |
| date issued | 2019 | |
| identifier uri | https://libsearch.um.ac.ir:443/fum/handle/fum/3368628?locale-attribute=en | |
| description abstract | In 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 |
| language | English | |
| title | Goodness of fit tests for Rayleigh distribution based on quantiles | en |
| type | Journal Paper | |
| contenttype | External Fulltext | |
| subject keywords | Goodness of fit test | en |
| subject keywords | Monte Carlo simulation | en |
| subject keywords | Quantile | en |
| subject keywords | Rayleigh distribution | en |
| identifier doi | 10.1080/03610918.2019.1651336 | |
| journal title | Communications in Statistics Part B: Simulation and Computation | fa |
| identifier link | https://profdoc.um.ac.ir/paper-abstract-1075753.html | |
| identifier articleid | 1075753 |