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### CGRANDOMWALD

CGRANDOMWALD
This function creates a vector of N random numbers using an Inverse Gaussian Distribution,
which is also known as the Wald Distribution. The reference for the code can be found at
http://en.wikipedia.org/wiki/Inverse_Gaussian_distribution.

Utility

## Params

seed: in, optional
The seed for the random number generator. If undefined, on output will
have the seed used by the IDL RandomU function. See the documentation
dims: in, optional, type=integer
A scalar or integer array defining the dimensions of the result. If no dimensions
are specified, a single random number is returned. If `Dims` is a scalar, a 1D vector
of that number of values will be returned.

## Keywords

mu: in, optional, type=double, default=1.0
The mean of the distribution.
lambda: in, optional, type=double, default=1.0
The shape parameter of the distribution. As lambda tends to infinity, the inverse
distribution becomes more like a normal distribution.

## Examples

For example, to create 100 random numbers, using the Wald distribution::
wald = cgRandomWald(seed, 100)
To create a 20-column by 10-row array of random numbers::
wald = cgRandoWald(seed, [20,10])

## Author

FANNING SOFTWARE CONSULTING::
David W. Fanning
1645 Sheely Drive
Fort Collins, CO 80526 USA
Phone: 970-221-0438
E-mail: david@idlcoyote.com
Coyote's Guide to IDL Programming: http://www.idlcoyote.com

## History

Written, 25 Oct 2012, by David W. Fanning.