A family of distribution is proposed by using Kumaraswamy-G ( Kw − G ) as the base line in generalized Marshall-Olkin (GMO) construction. By expanding probability density function and survival infinite series seen mixtures distribution. Series expansions for order statistics are also obtained. Moments, moment generating function, Rényi entropy, quantile random sample generation, asymptotes, shapes stochastic orderings investigated. Maximum likelihood estimation, their large standard error,...

We study a new family of distributions defined by the minimum Poisson random number independent and identically distributed variables having Topp Leone-G distribution.Some mathematical properties are derived.Maximum likelihood estimation model parameters is investigated.Two special models discussed.We perform three applications to real data sets show potentiality proposed family.In order test validity family, modified Chi-squared goodness-of-fit based on Nikulin-Rao-Robson statistics theoretically.

The aim of the article is to propose a unification generalized Marshall-Olkin (GMO) and Poisson-G (P-G) distributions into new family distributions. density survival function are expressed as infinite mixtures an exponentiated-P-G family. quantile function, asymptotes, shapes, stochastic ordering Rényi entropy derived. paper presents maximum likelihood estimation with large sample properties. A Monte Carlo simulation used examine pattern bias mean square error estimators. utility proposed...

A new family of continuous probability distributions is proposed by using Kumaraswamy-G distribution as the base line in Marshall-Olkin construction.A number known are derived particular cases.Various properties like formulation pdf different mixture exponentiated baseline distributions, order statistics, moments, moment generating function, Rényi entropy, quantile function and random sample generation have been investigated.Asymptotes, shapes stochastic ordering also...

This paper presents a new generalization of the extended Gompertz distribution. We defined so-called exponentiated generalized distribution, which has at least three important advantages: (i) Includes exponential, Gompertz, exponential and distributions as special cases; (ii) adds two parameters to base but does not use any complicated functions that end; (iii) its hazard function includes inverted bathtub shapes, are particularly because broad applicability in real-life situations. The work...

Unification of the recently introduced Kumaraswamy Marshall-Olkin-G and Beta family distributions is proposed. A number important statistical mathematical properties investigated. distribution belonging to proposed shown perform better than corresponding from by considering data fitting with three real life sets.   Key words: Exponentiated family, Power Weighted Moments, AIC K-S test.

bstract: In this article we propose further extension of the generalized Marshall Olkin-G ( GMO - G ) family distribution. The density and survival functions are expressed as infinite mixture Asymptotes, Rényi entropy, order statistics, probability weighted moments, moment generating function, quantile median, random sample generation parameter estimation investigated. Selected distributions from proposed compared with those four sub models well some other recently by considering real life...

We proposed a so-called Beta Kumaraswamy Burr Type X distribution which gives the extension of Kumaraswamy-G class family distribution. Some properties this model were provided, like: expansion densi- ties and quantile function. considered Bayes maximum likelihood methods to estimate parameters also simulate validate based on dierent set true values. real data sets employed show usefulness and  exibility serves as generalization many sub-models in elds engineering, medical, survival...

A new family of continuous distributions called the generalized odd linear exponential is proposed. The probability density and cumulative distribution function are expressed as infinite mixtures exponentiated-F distribution. Important statistical properties such quantile function, moment generating order statistics, moments, mean deviations, asymptotes stress–strength model proposed investigated. maximum likelihood estimation parameters presented. Simulation carried out for two mentioned...

In this article an attempt is made to introduce a new extension of the Fréchet model called Xgamma model. Some its properties are derived. The estimation parameters via different methods discussed. performances proposed investigated through simulations as well real life data sets. potentiality established modelling two results have shown clear preference for compared several know competing ones.

A new family of continuous distribution is proposed by using Kumaraswamy-G (Cordeiro and de Castro, 2011) as the base line in Marshal-Olkin (Marshall Olkin, 1997) construction. number known distributions are derived particular cases. Various properties like formulation pdf different mixture exponentiated baseline distributions, order statistics, moments, moment generating function, Renyi entropy, quantile function random sample generation have been investigated. Asymptotes, shapes stochastic...

A new generalization of the family Kumaraswamy-G (Cordeiro and de Castro, 2011) distribution that includes three recently proposed families namely Garhy generated (Elgarhy et al., 2016), Beta-Dagum Beta-Singh-Maddala (Domma Condino, 2016) is by constructing beta distribution. Useful expansions pdf cdf derived seen as infinite mixtures Order statistics, Probability weighted moments, moment generating function, R\'enyi entropies, quantile power series, random sample generation, asymptotes...

In this paper we propose a new family of distribution considering Generalized Marshal-Olkin as the base line in Beta-G Construction. The includes (Eugene et al. 2002 and Jones, 2004) (Jayakumar Mathew, 2008) families particular cases. Probability density function (pdf) cumulative (cdf) are expressed mixture (Marshal Olkin, 1997) distribution. Series expansions pdf order statistics also obtained. Moments, moment generating function, Rényi entropies, quantile power series, random sample...

We propose the McDonald Lindley-Poisson distribution and derive some of its mathematical properties including explicit expressions for moments, generating quantile functions, mean deviations, order statistics their moments. Its model parameters are estimated by maximum likelihood. A simulation study investigates performance estimates. The new represents a more flexible lifetime data analysis than other existing models as proved empirically means two real sets.

A new family called the Truncated Cauchy Power Kumaraswamy -G of distributions is proposed. Some special models this are introduced. Statistical properties such as expansion density function, moments, incomplete mean deviation, bonferroni and Lorenz curves We discuss method maximum likelihood to estimate model parameters study its performance by simulation. Real data sets modeled illustrate importance exibility proposed in comparison some known ones yielded favourable results.