Marshall-Olkin Alpha Power Weibull Distribution: Different Methods of Estimation Based on Type-I and Type-II Censoring

Ehab M. Almetwally; Mohamed A.H. Sabry; Randa Alharbi; Dalia Alnagar; Sh A.M. Mubarak; E. H. Hafez

doi:10.1155/2021/5533799

Marshall-Olkin Alpha Power Weibull Distribution: Different Methods of Estimation Based on Type-I and Type-II Censoring

Ehab M. Almetwally, Mohamed A.H. Sabry, Randa Alharbi, Dalia Alnagar, Sh A.M. Mubarak, E. H. Hafez

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

38 Scopus citations

Abstract

This paper introduces the new novel four-parameter Weibull distribution named as the Marshall-Olkin alpha power Weibull (MOAPW) distribution. Some statistical properties of the distribution are examined. Based on Type-I censored and Type-II censored samples, maximum likelihood estimation (MLE), maximum product spacing (MPS), and Bayesian estimation for the MOAPW distribution parameters are discussed. Numerical analysis using real data sets and Monte Carlo simulation are accomplished to compare various estimation methods. This novel model's supremacy upon some famous distributions is explained using two real data sets and it is shown that the MOAPW model can achieve better fits than other competitive distributions.

Original language	English
Article number	5533799
Journal	Complexity
Volume	2021
DOIs	https://doi.org/10.1155/2021/5533799
State	Published - 2021
Externally published	Yes

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title = "Marshall-Olkin Alpha Power Weibull Distribution: Different Methods of Estimation Based on Type-I and Type-II Censoring",

abstract = "This paper introduces the new novel four-parameter Weibull distribution named as the Marshall-Olkin alpha power Weibull (MOAPW) distribution. Some statistical properties of the distribution are examined. Based on Type-I censored and Type-II censored samples, maximum likelihood estimation (MLE), maximum product spacing (MPS), and Bayesian estimation for the MOAPW distribution parameters are discussed. Numerical analysis using real data sets and Monte Carlo simulation are accomplished to compare various estimation methods. This novel model's supremacy upon some famous distributions is explained using two real data sets and it is shown that the MOAPW model can achieve better fits than other competitive distributions.",

author = "Almetwally, \{Ehab M.\} and Sabry, \{Mohamed A.H.\} and Randa Alharbi and Dalia Alnagar and Mubarak, \{Sh A.M.\} and Hafez, \{E. H.\}",

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year = "2021",

doi = "10.1155/2021/5533799",

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volume = "2021",

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T2 - Different Methods of Estimation Based on Type-I and Type-II Censoring

AU - Almetwally, Ehab M.

AU - Sabry, Mohamed A.H.

AU - Alharbi, Randa

AU - Alnagar, Dalia

AU - Mubarak, Sh A.M.

AU - Hafez, E. H.

PY - 2021

Y1 - 2021

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AB - This paper introduces the new novel four-parameter Weibull distribution named as the Marshall-Olkin alpha power Weibull (MOAPW) distribution. Some statistical properties of the distribution are examined. Based on Type-I censored and Type-II censored samples, maximum likelihood estimation (MLE), maximum product spacing (MPS), and Bayesian estimation for the MOAPW distribution parameters are discussed. Numerical analysis using real data sets and Monte Carlo simulation are accomplished to compare various estimation methods. This novel model's supremacy upon some famous distributions is explained using two real data sets and it is shown that the MOAPW model can achieve better fits than other competitive distributions.

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JO - Complexity

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ER -

Marshall-Olkin Alpha Power Weibull Distribution: Different Methods of Estimation Based on Type-I and Type-II Censoring

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