The novel Kumaraswamy power Frechet distribution with data analysis related to diverse scientific areas

Najwan Alsadat; Aijaz Ahmad; Muzamil Jallal; Ahmed M. Gemeay; Mohammed A. Meraou; Eslam Hussam; Ehab M.Elmetwally; Md Moyazzem Hossain

doi:10.1016/j.aej.2023.03.003

The novel Kumaraswamy power Frechet distribution with data analysis related to diverse scientific areas

Najwan Alsadat, Aijaz Ahmad, Muzamil Jallal, Ahmed M. Gemeay, Mohammed A. Meraou, Eslam Hussam, Ehab M.Elmetwally, Md Moyazzem Hossain

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

Abstract

The study's major goal is to design a superior creative distribution by using the Kumaraswamy-G family of distributions to power Frechet distribution. The Kumaraswamy power Frechet distribution (KPFD) with four parameters is the full name of the revolutionary model. The distribution's probability density function may take numerous forms and graphs and can be used to describe complicated data sets efficiently. Several features of the new distribution are obtained, including dependability, hazard rate, quantile, and moments. The estimation of the unknown parameters of KPFD are provided using the KPFD maximum likelihood estimation technique. Furthermore, a study was performed using the Monte Carlo simulation approach to test estimator accuracy regarding average bias (AB) and mean square error (MSE). Last but not least, two genuine data sets are supplied to compare the proposed model to existing models.

Original language	English
Pages (from-to)	651-664
Number of pages	14
Journal	Alexandria Engineering Journal
Volume	70
DOIs	https://doi.org/10.1016/j.aej.2023.03.003
State	Published - 1 May 2023
Externally published	Yes

Keywords

Kumaraswamy-G family
Mean square error
Moments
Monte Carlo simulation
Power Frechet distribution
Renyi entropy

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10.1016/j.aej.2023.03.003

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title = "The novel Kumaraswamy power Frechet distribution with data analysis related to diverse scientific areas",

abstract = "The study's major goal is to design a superior creative distribution by using the Kumaraswamy-G family of distributions to power Frechet distribution. The Kumaraswamy power Frechet distribution (KPFD) with four parameters is the full name of the revolutionary model. The distribution's probability density function may take numerous forms and graphs and can be used to describe complicated data sets efficiently. Several features of the new distribution are obtained, including dependability, hazard rate, quantile, and moments. The estimation of the unknown parameters of KPFD are provided using the KPFD maximum likelihood estimation technique. Furthermore, a study was performed using the Monte Carlo simulation approach to test estimator accuracy regarding average bias (AB) and mean square error (MSE). Last but not least, two genuine data sets are supplied to compare the proposed model to existing models.",

keywords = "Kumaraswamy-G family, Mean square error, Moments, Monte Carlo simulation, Power Frechet distribution, Renyi entropy",

author = "Najwan Alsadat and Aijaz Ahmad and Muzamil Jallal and Gemeay, \{Ahmed M.\} and Meraou, \{Mohammed A.\} and Eslam Hussam and Ehab M.Elmetwally and Hossain, \{Md Moyazzem\}",

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year = "2023",

month = may,

day = "1",

doi = "10.1016/j.aej.2023.03.003",

language = "English",

volume = "70",

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journal = "Alexandria Engineering Journal",

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T1 - The novel Kumaraswamy power Frechet distribution with data analysis related to diverse scientific areas

AU - Alsadat, Najwan

AU - Ahmad, Aijaz

AU - Jallal, Muzamil

AU - Gemeay, Ahmed M.

AU - Meraou, Mohammed A.

AU - Hussam, Eslam

AU - M.Elmetwally, Ehab

AU - Hossain, Md Moyazzem

PY - 2023/5/1

Y1 - 2023/5/1

N2 - The study's major goal is to design a superior creative distribution by using the Kumaraswamy-G family of distributions to power Frechet distribution. The Kumaraswamy power Frechet distribution (KPFD) with four parameters is the full name of the revolutionary model. The distribution's probability density function may take numerous forms and graphs and can be used to describe complicated data sets efficiently. Several features of the new distribution are obtained, including dependability, hazard rate, quantile, and moments. The estimation of the unknown parameters of KPFD are provided using the KPFD maximum likelihood estimation technique. Furthermore, a study was performed using the Monte Carlo simulation approach to test estimator accuracy regarding average bias (AB) and mean square error (MSE). Last but not least, two genuine data sets are supplied to compare the proposed model to existing models.

AB - The study's major goal is to design a superior creative distribution by using the Kumaraswamy-G family of distributions to power Frechet distribution. The Kumaraswamy power Frechet distribution (KPFD) with four parameters is the full name of the revolutionary model. The distribution's probability density function may take numerous forms and graphs and can be used to describe complicated data sets efficiently. Several features of the new distribution are obtained, including dependability, hazard rate, quantile, and moments. The estimation of the unknown parameters of KPFD are provided using the KPFD maximum likelihood estimation technique. Furthermore, a study was performed using the Monte Carlo simulation approach to test estimator accuracy regarding average bias (AB) and mean square error (MSE). Last but not least, two genuine data sets are supplied to compare the proposed model to existing models.

KW - Kumaraswamy-G family

KW - Mean square error

KW - Moments

KW - Monte Carlo simulation

KW - Power Frechet distribution

KW - Renyi entropy

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DO - 10.1016/j.aej.2023.03.003

M3 - Article

AN - SCOPUS:85150243850

SN - 1110-0168

VL - 70

SP - 651

EP - 664

JO - Alexandria Engineering Journal

JF - Alexandria Engineering Journal

ER -

The novel Kumaraswamy power Frechet distribution with data analysis related to diverse scientific areas

Abstract

Keywords

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