2017
DOI: 10.1590/0001-3765201720150579
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The Extended Log-Logistic Distribution: Properties and Application

Abstract: We propose a new four-parameter lifetime model, called the extended log-logistic distribution, to generalize the two-parameter log-logistic model. The new model is quite flexible to analyze positive data. We provide some mathematical properties including explicit expressions for the ordinary and incomplete moments, probability weighted moments, mean deviations, quantile function and entropy measure. The estimation of the model parameters is performed by maximum likelihood using the BFGS algorithm. The flexibil… Show more

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Cited by 17 publications
(11 citation statements)
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“…In terms of applications, the log-logistic distribution and its generalizations have become the most popular models for survival and reliability data. Some recent applications have included: modeling for AIDS and Melanoma data (de Santana, Ortega, Cordeiro, & Silva, 2012); used for minification process (Gui, 2013); modeling breast cancer data (Ramos et al 2013); (Tahir et al 2014); modeling on censored survival data (Lemonte, 2014); modeling time up to first calving of cows (Louzada & Granzotto, 2016); modeling, inference, and use to a polled Tabapua Race Time up to First Calving Data (Granzotto et al 2017); modeling positive real data in many areas (Lima & Cordeiro, 2017); analysing a right-censored data (Shakhatreh, 2018); modeling lung cancer data (Alshangiti, et al 2016); and modeling of breaking stress data (Aldahlan, 2020).…”
Section: Extensions Of Log-logistic Distributionmentioning
confidence: 99%
See 1 more Smart Citation
“…In terms of applications, the log-logistic distribution and its generalizations have become the most popular models for survival and reliability data. Some recent applications have included: modeling for AIDS and Melanoma data (de Santana, Ortega, Cordeiro, & Silva, 2012); used for minification process (Gui, 2013); modeling breast cancer data (Ramos et al 2013); (Tahir et al 2014); modeling on censored survival data (Lemonte, 2014); modeling time up to first calving of cows (Louzada & Granzotto, 2016); modeling, inference, and use to a polled Tabapua Race Time up to First Calving Data (Granzotto et al 2017); modeling positive real data in many areas (Lima & Cordeiro, 2017); analysing a right-censored data (Shakhatreh, 2018); modeling lung cancer data (Alshangiti, et al 2016); and modeling of breaking stress data (Aldahlan, 2020).…”
Section: Extensions Of Log-logistic Distributionmentioning
confidence: 99%
“…the two parameters in (121) can add entropy to the center of the Exponentiated Generalized density or possible control both tail weights. Exponentiated generalized log-logistic distribution Lima and Cordeiro (2017) studied the mathematical and statistical properties of a new four-parameter survival model applying the exponentiated generalized (EG) class.…”
Section: Granzotto Et Al (2017) Introduced a New Parameter Induction Technique Of Generating Probability Distributions Calledmentioning
confidence: 99%
“…The data sets for East DWR (TDS mg l¯¹), Middle DWR (MCM) and West DWR (TDS mg l¯¹) follow log‐logistic (3P). The log‐logistic is a popular continuous probability distribution (Lima and Gauss, 2017) that is also known as the Fisk distribution (Fisk, 1961). Finally, the West DWR (MCM) follows the generalized extreme value distribution.…”
Section: Resultsmentioning
confidence: 99%
“…Degraded areas in the Amazon Basin with decreased soil organic matter impose multiple nutrient limitations restricting photochemical activities and plant growth [19,20]. Studies have demonstrated the effects of fertilization on biomass growth during forest restoration with leguminous trees [21,22]. Fertilization effects may enhance the drought tolerance of species due to increased quantum yield [23,24].…”
Section: Introductionmentioning
confidence: 99%