betapdf - Beta probability density function
Syntax
Y = betapdf(X,A,B)
Description
Y = betapdf(X,A,B) computes
the beta pdf at each of the values in X using the
corresponding parameters in A and B. X, A,
and B can be vectors, matrices, or multidimensional
arrays that all have the same size. A scalar input is expanded to
a constant array with the same dimensions of the other inputs. The
parameters in A and B must
all be positive, and the values in X must lie on
the interval [0, 1].
The beta probability density function for a given value x and
given pair of parameters a and b is
where B( · )
is the Beta function. The indicator function
ensures
that only values of x in the range (0 1)
have nonzero probability. The uniform distribution on (0 1)
is a degenerate case of the beta pdf where a = 1 and b = 1.
A likelihood function is the pdf viewed as a
function of the parameters. Maximum likelihood estimators (MLEs) are
the values of the parameters that maximize the likelihood function
for a fixed value of x.
Examples
a = [0.5 1; 2 4]
a =
0.5000 1.0000
2.0000 4.0000
y = betapdf(0.5,a,a)
y =
0.6366 1.0000
1.5000 2.1875
See Also
betacdf | betafit | betainv | betalike | betarnd | betastat | pdf
How To
 | betalike | | betarnd |  |
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