Re: need a good implementation of pseudorandom generators

two approaches might work
1) use SPSS to generate the random mumbers. The current version uses the Mersene Twister. The Marsaglia algorithm is also available as an option.
the are a few dozen transformation functions (rv.*) to create pseudorandom numbers that are "drawn from" various distributions.

2) code the algorithm
go to www.spss.com/support
click <login to online tech support>
click <login>
login as "guest" password "guest" click "ok"
click <spss>
click <documentation>
click <statistics>
click <algorithms>
click <Appendix 7: Generation of Random Numbers>

Art
Art@xxxxxxxxxxxxx
Social Research Consultants



nikhilbhargav_nsit@xxxxxxxxxxxxx wrote:

hi,

I am working on a sensor network optimization decision problem. I have
to perform a large number of simulations for it and require a good
pseudorandom generator for it.
I am currently using a suimple implementation based on rand() function.
But if i run the simulation 100 times then on all 100 times it gives
the same set of random values.
I require that the random variable say over an interval of 0.00 to 1.00
should be uniformly distributed and and if i run the simulation 1000
times than with high probability, all values in range [0.0,1.00] gets
covered.

Any pinters will help as my work is struck just because of this issue.


bye,

shiva

.

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