The distribution provides an alternative to the beta distribution such that it allows more density to be placed at the extremes of the bounded interval of support.
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This is relevant because the beta distribution is a suitable model for the random behavior of percentages and it is particularly suitable to the statistical modelling of proportions.
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It can however be represented by using a mixture density as the prior, here a combination of two beta distributions; this is a form of hyperprior.
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The stationary distribution of " Y " / " M " in this model is a beta distribution ( the beta inhibition model ).
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The beta-binomial distribution is the binomial distribution in which the probability of success at each trial is not fixed but random and follows the beta distribution.
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Asymptotically, the proportion of black and white balls will be distributed according to the Beta distribution, where each repetition of the experiment will produce a different value.
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The idea is to assume that " p " follows the beta distribution, find the talk ) 18 : 06, 6 September 2009 ( UTC)
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In the accompanying plots, the characteristic function of the beta distribution is displayed for symmetric ( ? = ? ) and skewed ( ? ` " ? ) cases.
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The ability of the beta distribution to take this great diversity of shapes ( using only two parameters ) is partly responsible for finding wide application for modeling actual measurements:
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From the expressions for the individual components, it follows that the determinant of Fisher's ( symmetric ) information matrix for the beta distribution with four parameters is:
