Difference between revisions of "BetaFn"
(Relationship to the GammaFn) |
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:<math>BetaFn(a,b) = \int_0^1 x^{a-1} (1-x)^{b-1} dx</math> | :<math>BetaFn(a,b) = \int_0^1 x^{a-1} (1-x)^{b-1} dx</math> | ||
− | == | + | The following relationship exists between the [[BetaFn]] and the [[GammaFn]]: |
− | + | :[[BetaFn]](a,b) = [[GammaFn]](a) * [[GammaFn]](b) / [[GammaFn]](a+b) | |
+ | |||
+ | == Numeric considerations == | ||
+ | |||
+ | For very large values of <code>a</code> and <code>b</code>, the result underflow, so that you might find it better to use <code>[[Ln]]([[BetaFn]](a,b))</code>. However, when computing the log-beta function, you should compute it using: | ||
+ | |||
+ | :<code>[[LGamma]](a) + [[LGamma]](b) - [[LGamma]](a+b)</code> | ||
== See Also == | == See Also == |
Latest revision as of 21:23, 5 February 2016
BetaFn(a, b)
The complete beta function, defined as:
- [math]\displaystyle{ BetaFn(a,b) = \int_0^1 x^{a-1} (1-x)^{b-1} dx }[/math]
The following relationship exists between the BetaFn and the GammaFn:
Numeric considerations
For very large values of a
and b
, the result underflow, so that you might find it better to use Ln(BetaFn(a,b))
. However, when computing the log-beta function, you should compute it using:
See Also
- Beta
- BetaI : The incomplete beta function
- GammaFn : The complete gamma function
- Parametric continuous distributions
- Distribution Densities Library
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