Type Ii Half Logisitic Exponentiated Lomax Distribution

1
bukoye_abdulwasiu
bukoye_abdulwasiu
2
Bukoye Abdulwasiu
Bukoye Abdulwasiu
3
Bada Olatunbosn
Bada Olatunbosn
4
Muritala Abdulkabir
Muritala Abdulkabir
5
Ajadi
Ajadi
6
A.Akeem
A.Akeem

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GJSFR Volume 21 Issue F3

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In this paper, we introduces a new distribution called Type II half logistic exponentiated lomax (TIIHLEE) distribution established from Type II half logistic G family of distribution We investigate some of its mathematical and statistical properties such as the explicit form of the ordinary moments, moment generating function, conditional moments, mean deviations, residual life and Renyi entropy. The maximum likelihood method is used to estimate the model parameters. Simulation studies were conducted to assess the finite sample behavior of the maximum likelihood estimators. Finally, we illustrate the importance and applicability of the model by the study of two real data sets.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

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Not applicable for this article.

bukoye_abdulwasiu. 2021. \u201cType Ii Half Logisitic Exponentiated Lomax Distribution\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 21 (GJSFR Volume 21 Issue F3): .

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GJSFR Volume 21 Issue F3
Pg. 49- 71
Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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GJSFR-F Classification: MSC 2010: 11D61
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v1.2

Issue date

July 2, 2021

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English

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In this paper, we introduces a new distribution called Type II half logistic exponentiated lomax (TIIHLEE) distribution established from Type II half logistic G family of distribution We investigate some of its mathematical and statistical properties such as the explicit form of the ordinary moments, moment generating function, conditional moments, mean deviations, residual life and Renyi entropy. The maximum likelihood method is used to estimate the model parameters. Simulation studies were conducted to assess the finite sample behavior of the maximum likelihood estimators. Finally, we illustrate the importance and applicability of the model by the study of two real data sets.

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Type Ii Half Logisitic Exponentiated Lomax Distribution

Bukoye Abdulwasiu
Bukoye Abdulwasiu
Bada Olatunbosn
Bada Olatunbosn
Muritala Abdulkabir
Muritala Abdulkabir
Ajadi
Ajadi
A.Akeem
A.Akeem

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