<< distfun_gampdf Gamma distfun_gamstat >>

Distfun >> Distfun > Gamma > distfun_gamrnd

distfun_gamrnd

Gamma random numbers

Calling Sequence

R = distfun_gamrnd ( a , b )
R = distfun_gamrnd ( a , b , [m,n] )
R = distfun_gamrnd ( a , b , m , n )

Parameters

a :

a n-by-m matrix of doubles, the shape parameter, a>0.

b :

a n-by-m matrix of doubles, the scale parameter, b>0.

m :

a 1x1 matrix of floating point integers, the number of rows of R

n :

a 1x1 matrix of floating point integers, the number of columns of R

R:

a matrix of doubles, the positive random numbers.

Description

Generates random variablesfrom the Gamma distribution function.

Any scalar input argument is expanded to a matrix of doubles of the same size as the other input arguments.

Examples

// Set the seed so as to always get the same results.
distfun_seedset(1);

// Use R = distfun_gamrnd ( a , b )
distfun_gamrnd(1:6,(1:6)^-1)
distfun_gamrnd(1:6,1)
distfun_gamrnd(1,(1:6)^-1)

// Check R = distfun_gamrnd ( a , b , v )
computed = distfun_gamrnd(2,1,[1 5])
computed = distfun_gamrnd(2,1,[3 2])

// Check mean and variance for R = distfun_gamrnd ( a , b )
N = 1000;
a = 2;
b = 3;
[M,V] = distfun_gamstat ( a , b )
computed = distfun_gamrnd(2,3,[1 N]);
Mc = mean(computed)
Mv = variance(computed)

// Check R = distfun_gamrnd ( a , b , m , n )
computed = distfun_gamrnd([1 2 3;4 5 6],0.1,2,3)
computed = distfun_gamrnd(2,1,2,3)
computed = distfun_gamrnd(1,[1 2 3;4 5 6],2,3)

// Make a plot of the actual distribution of the numbers
a = 2;
b = 3;
data = distfun_gamrnd(a,b,1,1000);
scf();
histplot(10,data)
x = linspace(0,30,1000);
y = distfun_gampdf(x,a,b);
plot(x,y)
xtitle("Gamma Random Numbers","X","Density")
legend(["Empirical","PDF"]);

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