beta distribution - Maple Help

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Statistics[Distributions][Beta] - beta distribution

 Calling Sequence 'Beta'(nu, omega) BetaDistribution(nu, omega)

Parameters

 nu - first shape parameter omega - second shape parameter

Description

 • The beta distribution is a continuous probability distribution with probability density function given by:

$f\left(t\right)=\left\{\begin{array}{cc}0& t<0\\ \frac{{t}^{-1+\mathrm{\nu }}{\left(1-t\right)}^{-1+\mathrm{\omega }}}{\mathrm{Β}\left(\mathrm{\nu },\mathrm{\omega }\right)}& t<1\\ 0& \mathrm{otherwise}\end{array}\right\$

 subject to the following conditions:

$0<\mathrm{\nu },0<\mathrm{\omega }$

 • The beta distribution is related to the independent Gamma variates Gamma(1,nu) and Gamma(1,omega) by the formula Beta(nu,omega) ~ Gamma(1,nu)/(Gamma(1,nu)+Gamma(1,omega)).
 • Note that the Beta(a, b) returns the value of the Beta function  with parameters a and b, so in order to define a Beta random variable one should use the unevaluated name 'Beta'. In 2D math notation, the capital letter $\mathrm{Β}$ looks like a capital letter $B$, but the two are different in Maple.

Examples

 > $\mathrm{with}\left(\mathrm{Statistics}\right):$

The following is invalid.

 > $\mathrm{RandomVariable}\left(\mathrm{Β}\left(1,2\right)\right)$

Alternatives are:

 > $\mathrm{RandomVariable}\left('\mathrm{Β}'\left(1,2\right)\right)$
 ${\mathrm{_R}}$ (1)

and

 > $\mathrm{RandomVariable}\left(\mathrm{BetaDistribution}\left(1,2\right)\right)$
 ${\mathrm{_R0}}$ (2)
 > $X:=\mathrm{RandomVariable}\left('\mathrm{Β}'\left(\mathrm{ν},\mathrm{ω}\right)\right):$
 > $\mathrm{PDF}\left(X,u\right)$
 ${{}\begin{array}{cc}{0}& {u}{<}{0}\\ \frac{{{u}}^{{-}{1}{+}{\mathrm{ν}}}{}{\left({1}{-}{u}\right)}^{{-}{1}{+}{\mathrm{ω}}}}{{\mathrm{Β}}{}\left({\mathrm{ν}}{,}{\mathrm{ω}}\right)}& {u}{<}{1}\\ {0}& {\mathrm{otherwise}}\end{array}$ (3)
 > $\mathrm{PDF}\left(X,0.5\right)$
 $\frac{{{0.5}}^{{-}{1.}{+}{\mathrm{ν}}}{}{{0.5}}^{{-}{1.}{+}{\mathrm{ω}}}}{{\mathrm{Β}}{}\left({\mathrm{ν}}{,}{\mathrm{ω}}\right)}$ (4)
 > $\mathrm{Mean}\left(X\right)$
 $\frac{{\mathrm{ν}}}{{\mathrm{ν}}{+}{\mathrm{ω}}}$ (5)
 > $\mathrm{Variance}\left(X\right)$
 $\frac{{\mathrm{ν}}{}{\mathrm{ω}}}{{\left({\mathrm{ν}}{+}{\mathrm{ω}}\right)}^{{2}}{}\left({\mathrm{ν}}{+}{\mathrm{ω}}{+}{1}\right)}$ (6)