Section: Random Number Generation
y = randgamma(a,r),
where a
and r
are vectors describing the parameters of the
gamma distribution. Roughly speaking, if a
is the mean time between
changes of a Poisson random process, and we wait for the r
change,
the resulting wait time is Gamma distributed with parameters a
and r
.
r
-th event in a process with
mean time a
between events. The probability distribution of a Gamma
random variable is
Note also that for integer values of r
that a Gamma random variable
is effectively the sum of r
exponential random variables with parameter
a
.
randgamma
function to generate Gamma-distributed
random variables, and then generate them again using the randexp
function.
--> randgamma(1,15*ones(1,9)) ans = 10.0227 12.4783 18.0388 21.7056 14.1249 15.9260 22.0177 15.9170 24.3781 --> sum(randexp(ones(15,9))) ans = 14.5031 12.8908 10.5201 16.9976 9.8463 12.7479 13.6879 21.7005 11.4172