2023
DOI: 10.1007/s44199-023-00056-6
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Marshall Olkin Exponentiated Dagum Distribution: Properties and Applications

Abstract: Marshall Olkin Exponentiated Dagum distribution (MOED) with four shape parameters and one scale parameter is proposed. Alternative expressions are derived for the newly proposed distribution to sort out lengthy calculations. Various properties of MOED are derived, including the measure of central tendency, the measure of dispersion, hazard rate and survival rate are also derived for the MOED. Moreover, the network properties are also derived, including moments, moment generating function, quantile function, me… Show more

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Cited by 3 publications
(2 citation statements)
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“…For example, [4] proposed the Topp-Leone Marshall-Olkin-G family of distributions, which is a flexible model capable of effectively handling heavy-tailed data and various hazard rate functions. The Marshall Olkin Exponentiated Dagum (MOED) distribution has also been applied to real-life datasets and has yielded encouraging results [5]. Furthermore, the Marshall-Olkin-odd power generalized Weibull (MO-OPGW-G) distribution is suitable for analyzing covid-19 data [6], while the Marshall-Olkin-Type II-Topp-Leone-G (MO-TII-TL-G) family of distributions exhibits power-law behavior, which is a common characteristic observed in real-life datasets [7].…”
Section: Introductionmentioning
confidence: 99%
“…For example, [4] proposed the Topp-Leone Marshall-Olkin-G family of distributions, which is a flexible model capable of effectively handling heavy-tailed data and various hazard rate functions. The Marshall Olkin Exponentiated Dagum (MOED) distribution has also been applied to real-life datasets and has yielded encouraging results [5]. Furthermore, the Marshall-Olkin-odd power generalized Weibull (MO-OPGW-G) distribution is suitable for analyzing covid-19 data [6], while the Marshall-Olkin-Type II-Topp-Leone-G (MO-TII-TL-G) family of distributions exhibits power-law behavior, which is a common characteristic observed in real-life datasets [7].…”
Section: Introductionmentioning
confidence: 99%
“…Statistical distributions play a crucial role in statistics, probability theory, and various domains of science and engineering in describing and predicting the characteristics of natural phenomena. However, the classical probability distributions do not always adequately capture many naturally existing asymmetric data sets [1]. To overcome this limitation, there is a need to enhance the flexibility of existing distributions in modeling data, particularly in reliability analysis, where the hazard rate can have various shapes.…”
Section: Introductionmentioning
confidence: 99%