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
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 for RandomU for additional information. 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.
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.
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])
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
Written, 25 Oct 2012, by David W. Fanning.
Copyright (c) 2012, Fanning Software Consulting, Inc.