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Further results involving Marshall-Olkin log-logistic distribution: reliability analysis, estimation of the parameter, and applications.

Alshangiti AM, Kayid M, Alarfaj B - Springerplus (2016)

Bottom Line: This model is both useful and practical in areas such as reliability and life testing.Maximum likelihood estimation of the parameters of the model is discussed.Finally, a real data set is analyzed and it is observed that the presented model provides a better fit than the log-logistic model.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451 Kingdom of Saudi Arabia.

ABSTRACT
The purpose of this paper is to provide further study of the Marshall-Olkin log-logistic model that was first described by Gui (Appl Math Sci 7:3947-3961, 2013). This model is both useful and practical in areas such as reliability and life testing. Some statistical and reliability properties of this model are presented including moments, reversed hazard rate and mean residual life functions, among others. Maximum likelihood estimation of the parameters of the model is discussed. Finally, a real data set is analyzed and it is observed that the presented model provides a better fit than the log-logistic model.

No MeSH data available.


Plot of the variance of M–O log-logistic for different value of  and ,
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Fig6: Plot of the variance of M–O log-logistic for different value of and ,

Mentions: In general, the last integrals cannot be given explicitly in terms of . The mean E(X) and the variance Var(X) of M–O log-logistic are shown graphically in Figs. 5 and 6 for different value of and , . These figures show the mean and variance increase as the value of increases.Fig. 5


Further results involving Marshall-Olkin log-logistic distribution: reliability analysis, estimation of the parameter, and applications.

Alshangiti AM, Kayid M, Alarfaj B - Springerplus (2016)

Plot of the variance of M–O log-logistic for different value of  and ,
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4814396&req=5

Fig6: Plot of the variance of M–O log-logistic for different value of and ,
Mentions: In general, the last integrals cannot be given explicitly in terms of . The mean E(X) and the variance Var(X) of M–O log-logistic are shown graphically in Figs. 5 and 6 for different value of and , . These figures show the mean and variance increase as the value of increases.Fig. 5

Bottom Line: This model is both useful and practical in areas such as reliability and life testing.Maximum likelihood estimation of the parameters of the model is discussed.Finally, a real data set is analyzed and it is observed that the presented model provides a better fit than the log-logistic model.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451 Kingdom of Saudi Arabia.

ABSTRACT
The purpose of this paper is to provide further study of the Marshall-Olkin log-logistic model that was first described by Gui (Appl Math Sci 7:3947-3961, 2013). This model is both useful and practical in areas such as reliability and life testing. Some statistical and reliability properties of this model are presented including moments, reversed hazard rate and mean residual life functions, among others. Maximum likelihood estimation of the parameters of the model is discussed. Finally, a real data set is analyzed and it is observed that the presented model provides a better fit than the log-logistic model.

No MeSH data available.