rndPoisson¶
Purpose¶
Computes Poisson pseudo-random numbers with a choice of underlying random number generator.
Format¶
-
x =
rndPoisson
(r, c, lambda)¶ -
{ x, newstate } =
rndPoisson
(r, c, lambda, state) - Parameters:
r (scalar) – number of rows of resulting matrix.
c (scalar) – number of columns of resulting matrix.
lambda (matrix, vector or scalar) – mean parameter for Poisson distribution, ExE conformable matrix with r and c.
state (scalar or opaque vector) –
Optional argument.
scalar case
state = starting seed value only. If -1, GAUSS computes the starting seed based on the system clock.
opaque vector case
state = the state vector returned from a previous call to one of the
rnd
random number functions.
- Returns:
x (r x c matrix) – Poisson distributed random numbers.
newstate (Opaque vector) – the updated state.
Examples¶
The example below simulates 100 observations of a Poisson process with a mean of 17.
lambda = 17;
x = rndPoisson(100, 1, lambda);
Remarks¶
The properties of the pseudo-random numbers in x are:
r and c will be truncated to integers if necessary.
Technical Notes¶
The default generator for rndPoisson()
is the SFMT Mersenne-Twister 19937.
You can specify a different underlying random number generator with the
function rndCreateState()
.
See also
Functions rndCreateState()
, rndStateSkip()