Main Content

randg

Gamma random numbers with unit scale

Syntax

Y = randg
Y = randg(A)
Y = randg(A,m)
Y = randg(A,m,n,p,...)
Y = randg(A,[m,n,p,...])
Y = randg(...,classname)
Y = randg(...,'like',X)
Y = randg(...,'like',classname)

Description

Y = randg returns a scalar random value chosen from a gamma distribution with unit scale and shape.

Y = randg(A) returns a matrix of random values chosen from gamma distributions with unit scale. Y is the same size as A, and randg generates each element of Y using a shape parameter equal to the corresponding element of A.

Y = randg(A,m) returns an m-by-m matrix of random values chosen from gamma distributions with shape parameters A. A is either an m-by-m matrix or a scalar. If A is a scalar, randg uses that single shape parameter value to generate all elements of Y.

Y = randg(A,m,n,p,...) or Y = randg(A,[m,n,p,...]) returns an m-by-n-by-p-by-... array of random values chosen from gamma distributions with shape parameters A. A is either an m-by-n-by-p-by-... array or a scalar.

Y = randg(...,classname) returns an array of random values chosen from gamma distributions of the specified class. classname can be double or single.

Y = randg(...,'like',X) or Y = randg(...,'like',classname) returns an array of random values chosen from gamma distributions of the same class as X or classname, respectively. X is a numeric array.

randg produces pseudo-random numbers using the MATLAB® functions rand and randn. The sequence of numbers generated is determined by the settings of the uniform random number generator that underlies rand and randn. Control that shared random number generator using rng. See the rng documentation for more information.

Note

To generate gamma random numbers and specify both the scale and shape parameters, you should call gamrnd.

Examples

Example 1

Generate a 100-by-1 array of values drawn from a gamma distribution with shape parameter 3. 

r = randg(3,100,1);

Example 2

Generate a 100-by-2 array of values drawn from gamma distributions with shape parameters 3 and 2.

A = [ones(100,1)*3,ones(100,1)*2];
r = randg(A,[100,2]);

Example 3

To create reproducible output from randg, reset the random number generator used by rand and randn to its default startup settings. This way randg produces the same random numbers as if you restarted MATLAB. 

rng('default')
randg(3,1,5)

ans =

    6.9223    4.3369    1.0505    3.2662   11.3269

Example 4

Save the settings for the random number generator used by rand and randn, generate 5 values from randg, restore the settings, and repeat those values. 

s = rng; % Obtain the current state of the random stream
r1 = randg(10,1,5)

r1 =

    9.4719    9.0433   15.0774   14.7763    6.3775

rng(s); % Reset the stream to the previous state
r2 = randg(10,1,5)

r2 =

    9.4719    9.0433   15.0774   14.7763    6.3775

r2 contains exactly the same values as r1.

Example 5

Reinitialize the random number generator used by rand and randn with a seed based on the current time. randg returns different values each time you do this. Note that it is usually not necessary to do this more than once per MATLAB session. 

rng('shuffle');
randg(2,1,5);

References

[1] Marsaglia, G., and W. W. Tsang. “A Simple Method for Generating Gamma Variables.” ACM Transactions on Mathematical Software. Vol. 26, 2000, pp. 363–372.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Version History

Introduced before R2006a

See Also