# Beta PDF

(Difference between revisions)
 Revision as of 08:59, 27 July 2007 (view source)Hannes79 (Talk | contribs)← Older edit Latest revision as of 10:05, 17 December 2008 (view source)Peter (Talk | contribs) m (Reverted edits by ChierBasal (Talk) to last version by Hannes79) (2 intermediate revisions not shown) Line 6: Line 6: The beta function PDF has the form The beta function PDF has the form :$:[itex] - P (\eta) = \frac{\eta^\{alpha-1} (1- \eta)^{\beta-1}}{\Gamma(\alpha) \Gamma(\beta)} + P (\eta) = \frac{\eta^{\alpha-1} (1- \eta)^{\beta-1}}{\Gamma(\alpha) \Gamma(\beta)} \Gamma(\alpha + \beta) \Gamma(\alpha + \beta)$ [/itex]

## Latest revision as of 10:05, 17 December 2008

A $\beta$ probability density function depends on two moments only; the mean $\mu$ and the variance $\sigma$. 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

$P (\eta) = \frac{\eta^{\alpha-1} (1- \eta)^{\beta-1}}{\Gamma(\alpha) \Gamma(\beta)} \Gamma(\alpha + \beta)$

where $\Gamma$ is the gamma function and the parameters $\alpha$ and $\beta$ are related through

$\alpha = \mu \gamma$
$\beta = (1- \mu) \gamma$

where $\gamma$ is

$\gamma = \frac{\mu (1- \mu)}{\sigma} -1$