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  2. Beta prime distribution - Wikipedia

    en.wikipedia.org/wiki/Beta_prime_distribution

    In probability theory and statistics, the beta prime distribution (also known as inverted beta distribution or beta distribution of the second kind [1]) is an absolutely continuous probability distribution. If [,] has a beta distribution, then the odds has a beta prime distribution.

  3. Beta distribution - Wikipedia

    en.wikipedia.org/wiki/Beta_distribution

    The formulation of the beta distribution discussed here is also known as the beta distribution of the first kind, whereas beta distribution of the second kind is an alternative name for the beta prime distribution. The generalization to multiple variables is called a Dirichlet distribution.

  4. Generalized beta distribution - Wikipedia

    en.wikipedia.org/wiki/Generalized_Beta_distribution

    The beta family includes the beta of the first and second kind [7] (B1 and B2, where the B2 is also referred to as the Beta prime), which correspond to c = 0 and c = 1, respectively. Setting =, = yields the standard two-parameter beta distribution.

  5. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The uniform distribution or rectangular distribution on [a,b], where all points in a finite interval are equally likely, is a special case of the four-parameter Beta distribution. The Irwin–Hall distribution is the distribution of the sum of n independent random variables, each of which having the uniform distribution on [0,1].

  6. F-distribution - Wikipedia

    en.wikipedia.org/wiki/F-distribution

    The F-distribution is a particular parametrization of the beta prime distribution, which is also called the beta distribution of the second kind. The characteristic function is listed incorrectly in many standard references (e.g., [3]). The correct expression [7] is

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  9. Noncentral beta distribution - Wikipedia

    en.wikipedia.org/wiki/Noncentral_beta_distribution

    The Type I cumulative distribution function is usually represented as a Poisson mixture of central beta random variables: [1] = = (+,),where λ is the noncentrality parameter, P(.) is the Poisson(λ/2) probability mass function, \alpha=m/2 and \beta=n/2 are shape parameters, and (,) is the incomplete beta function.