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.

Categories

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    Utility
   

Params

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    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.
     

Keywords

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    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

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    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

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    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

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

Copyright

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    Copyright (c) 2012, Fanning Software Consulting, Inc.