beta distribution

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beta distribution

[′bād·ə dis·trə′byü·shən]
(statistics)
The probability distribution of a random variable with density function ƒ(x) = [x α-1(1-x)β-1]/ B (α,β), where B represents the beta function, α and β are positive real numbers, and 0<x<1. Also known as Pearson Type I distribution.
References in periodicals archive ?
Figure 1 illustrates the flexibility of the beta distribution for modeling pass rates from 0 to 1 for various values of [alpha] and [beta].
In the second step, LRT comparison was made with a null model M7, assuming a beta distribution B (p, q) for x w (in the interval 0 < [omega] < 1, where 0 indicated complete constraint and 1 was the expectation under no selection pressure), and another M8 model using an additional class of sites with w estimated was included.
The gamma function, the extended gamma function, the beta function, the extended beta function, the gamma distribution, the beta distribution and the extended beta distribution have been generalized to the matrix case in various ways.
In (Chia, Hutchinson 1991) beta distribution is offered as a model for frequency distribution of daily cloud duration.
We chose the beta distribution as the prior for proportions and normal distribution as the prior for lnRR (natural logarithm of RR); we used the moment method on the reported prior modes to determine the bias distribution parameters.
The beta distribution is a member of continuous probability distributions defined on the interval (0, 1) with two positive parameters, including a and
Generalized Beta distribution of second kind (GB2) is considered in order to model the income distribution of Punjab province for the year 2004 and 2008.
It should be noted that, with the above specific probabilities, the residues distributed by normal distribution indicated the reference population, whereas the residues generated by Beta distribution corresponded to outliers.
The experiments showed that beta distribution, with probability density function
The beta distribution is parsimonious and flexible when applying expert judgments.

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