2014
DOI: 10.1186/s40488-014-0017-1
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The Kumaraswamy-geometric distribution

Abstract: In this paper, the Kumaraswamy-geometric distribution, which is a member of the T-geometric family of discrete distributions is defined and studied. Some properties of the distribution such as moments, probability generating function, hazard and quantile functions are studied. The method of maximum likelihood estimation is proposed for estimating the model parameters. Two real data sets are used to illustrate the applications of the Kumaraswamy-geometric distribution.

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Cited by 25 publications
(12 citation statements)
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“…(21). Akinsete et al (2014) also proved that this distribution can also be derived by considering log-Kumararswamy distribution instead of Kuamarswamy distribution and taking W(x) = − log(1 − x).…”
Section: Marshall and Olkin Followed By Method-iiimentioning
confidence: 99%
See 1 more Smart Citation
“…(21). Akinsete et al (2014) also proved that this distribution can also be derived by considering log-Kumararswamy distribution instead of Kuamarswamy distribution and taking W(x) = − log(1 − x).…”
Section: Marshall and Olkin Followed By Method-iiimentioning
confidence: 99%
“…(19) when W(x) = − log(1 − x). Akinsete et al (2014) considered T as the Kumaraswamy (1980) distribution with cdf…”
Section: Marshall and Olkin Followed By Method-iiimentioning
confidence: 99%
“…The method of generalization of distributions by the Kumaraswamy-G generator proposed by [1] is one of the preferable techniques in distribution theory and was considered by many authors in recent years. For instance, the Kumaraswamy-Weibull distribution [2], Kumaraswamy binomial [3], Kumaraswamy generalized gamma [4], Kumaraswamy-Gumbel [5], Kumaraswamy generalized half-normal [6], Kumaraswamy log-logistic [7], Kumaraswamy-Birnbaum-Saunders [8], Kumaraswamy inverse Weibull [9], Kumaraswamy double inverse exponential [10], Kumaraswamy power series [11], Kumaraswamy-Pareto [12], Kumaraswamy generalized linear failure rate [13], Kumaraswamy exponentiated Pareto [14], Kumaraswamy quasi-Lindley [15], Kumaraswamy generalized Pareto [16], Kumaraswamy-Burr XII distribution [17], Kumaraswamy generalized exponentiated Pareto [18], Kumaraswamy generalized Lomax [19], Kumaraswamy geometric [20], Kumaraswamy half-Cauchy distrbution [21], Kumaraswamy generalized Rayleigh [22], Kumaraswamy-Dagum distribution [23], Kumaraswamy inverse Rayleigh [24], Kumaraswamy inverse exponential [25], Kumaraswamy -Kumaraswamy [26], Kumaraswamy transmuted exponentiated modified Weibull [27], Kumaraswamy odd loglogistic [28], Kumaraswamy skew-normal [29].…”
Section: Introductionmentioning
confidence: 99%
“…Using (8), a number of modifications of the existing distributions have been proposed in the literature. A brief list of these modifications is presented in Table 3: Eugene et al (2002) introduced the beta generated method that uses the beta distribution with parameters a and b as the generator to develop the beta generated distributions.…”
Section: Kumaraswamy-g Family Of Distributionsmentioning
confidence: 99%