Beta PDF
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The beta function PDF has the form | The beta function PDF has the form | ||
:<math> | :<math> | ||
- | P (\eta) = \frac{\eta^\alpha (1- \eta)^{\beta-1}}{\Gamma(\alpha) \Gamma(\beta)} | + | P (\eta) = \frac{\eta^\{alpha-1} (1- \eta)^{\beta-1}}{\Gamma(\alpha) \Gamma(\beta)} |
\Gamma(\alpha + \beta) | \Gamma(\alpha + \beta) | ||
</math> | </math> |
Revision as of 08:59, 27 July 2007
A probability density function depends on two moments only; the mean and the variance . This function is widely used in turbulent combustion to define the scalar distribution at each computational point as a function of the mean and variance. Assuming that the sample space of the scalar varies betwen 0 and 1. The beta function PDF has the form
- Failed to parse (syntax error): P (\eta) = \frac{\eta^\{alpha-1} (1- \eta)^{\beta-1}}{\Gamma(\alpha) \Gamma(\beta)} \Gamma(\alpha + \beta)
where is the gamma function and the parameters and are related through
where is