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Subject: Re: Difference of 2 CDF functions
Date: Fri, 13 Mar 2009 02:56:01 +0000 (UTC)
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"Themis " <thkountouris@hotmail.com> wrote in message <gpc9g5$crs$1@fred.mathworks.com>...
> Yes you are right, there is an error in that equation. i should have been n.
> Also k is ussualy taken as k=3. M and N are the inputs here and the process is calculated for all values of m.
> The end result is M-1 values, which appear to be normaly distributed.

  Aha!  The fog begins to clear.  You will have to proceed with some care.  This presumed convergence to a normal distribution is probably analogous to that given by the famous central limit theorem for the sum of many successive independent values of a random variable.  It is necessary to carefully rescale and translate the independent variable values - in this case the m values - to smaller and smaller values as M increases so as to force the mean and variance to approach that of the given normal distribution.  Then if your surmise is correct, the respective cdf's will also converge.

  But again, it is useless to generate random normally distributed variables when the distribution is already thoroughly understood.

Roger Stafford