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  1. The Pareto distribution has long been recognized as a suitable model for many non-negative socio-economic variables. Univariate and multivariate variations abound. Some unification is possible by representing ...

    Authors: Barry C Arnold

    Citation: Journal of Statistical Distributions and Applications 2014 1:11

    Content type: Review

    Published on:

  2. Biological fitness is typically measured by the expected rate of reproduction, but strategies with high fitness can also have high probabilities of extinction. Likewise, gambling strategies with a high expecte...

    Authors: Sterling Sawaya and Steffen Klaere

    Citation: Journal of Statistical Distributions and Applications 2014 1:10

    Content type: Research

    Published on:

  3. We introduce a new class of models called the Marshall-Olkin extended Weibull family of distributions based on the work by Marshall and Olkin (Biometrika 84:641–652, 1997). The proposed family includes as spec...

    Authors: Manoel Santos-Neto, Marcelo Bourguignon, Luz M Zea, Abraão DC Nascimento and Gauss M Cordeiro

    Citation: Journal of Statistical Distributions and Applications 2014 1:9

    Content type: Research

    Published on:

  4. Based on the trivariate pair-copula construction for the bivariate linear circular copula by Perlman and Wellner (Symmetry 3:574-99, 2011) and the Theorem of Carathéodory, which states that any valid correlati...

    Authors: Werner Hürlimann

    Citation: Journal of Statistical Distributions and Applications 2014 1:7

    Content type: Methodology

    Published on:

  5. The distribution theory of runs and patterns has been successfully used in a variety of applications including, for example, nonparametric hypothesis testing, reliability theory, quality control, DNA sequence ...

    Authors: Brad C Johnson and James C Fu

    Citation: Journal of Statistical Distributions and Applications 2014 1:5

    Content type: Research

    Published on:

  6. The cumulative distribution function (CDF) of the T-X family is given by R{W(F(x))}, where R is the CDF of a random variable T, F is the CDF of X and W is an increasing function defined on [0, 1] having the suppo...

    Authors: Mohammad A Aljarrah, Carl Lee and Felix Famoye

    Citation: Journal of Statistical Distributions and Applications 2014 1:2

    Content type: Research

    Published on:

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