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@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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