Mmm ..random number generation is a massive subject 
never too far from a practitioners mind, is it.
Its always attached to a question mark with me.
Full marks are surely due to the wizards behind the reseach.
In one sentence or two, do you know, please what tests are 
used to demonstrate randomness
of the output observations ?
Just asking, is all.
Thanks everybody
Best regards from Richard Hudson
Dr RJF Hudson Qld Australia 
rjfhud(a)powerup.com.au
  ----- Original Message ----- 
  From: Allin Cottrell 
  To: Gretl users 
  Sent: Saturday, January 15, 2011 2:12 AM
  Subject: [Gretl-users] the gretl RNG
  For some years now the random number generator (RNG) used in gretl
  has been the Mersenne Twister as implemented in the GLib library.
  We've recently been investigating an alternative, namely the
  SIMD-oriented Fast Mersenne Twister (SFMT); see
  
http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/
  We find that this new variant is faster, has better
  equidistributional properties, and exhibits quicker recovery from
  poor initialization. We're therefore going to make SFMT the
  default RNG in gretl: this will be in the next release (gretl
  1.9.4) and will land in CVS and the snapshots for Windows and Mac
  shortly.
  This change is (necessarily) backward incompatible, in the sense
  that a gretl script that calls for random values using a specified
  seed will now produce a different series of random values from
  before. However, to preserve compatibility for anyone who wants to
  replicate previous studies exactly, you will be able to call for
  use of the old gretl RNG. The command to do this will be
  set RNG MT
  Having done that, you can switch back to the new default via
  set RNG SFMT
  Allin Cottrell
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