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rnorm.halton

3 messages · Anirban Mukherjee, David Winsemius, Christophe Dutang

Original
Anirban Mukherjee
# 
Thanks everyone for your replies. Particularly David.

The numbers are pseudo-random. Repeated calls should/would give the
same output. Currently, Halton works fine when used to just get the
Halton sequence, but the random deviates call is not working in 64 bit
R. For now, I will generate the numbers in 32 bit R, save them and
then load them back in when using 64 bit R. The package maintainers
can look at it if/when they get a chance and/or access to 64 bit R.

Thanks!

Best,
Anirban
On Tue, Sep 15, 2009 at 9:01 AM, David Winsemius <dwinsemius at comcast.net> wrote:

  
    

      
      
    

  


  


    

    

      
      

        


  

        

      David Winsemius
    

    

      
      #
    

  


  

      
On Sep 15, 2009, at 11:10 AM, Anirban Mukherjee wrote:

        

            

      
      
      
    

        
As I said, this package is not one with which I have experience. It  
has _not_ however the case that repeated calls to (typical?) random  
number functions give the same output when called repeatedly:

 > rnorm(10)
  [1] -0.8740195  2.1827411 -0.1473012 -1.4406262  0.1820631  
-1.3151244 -0.4813703  0.8177692
  [9]  0.2076117  1.8697418
 > rnorm(10)
  [1] -0.7725731  0.8696742 -0.4907099  0.1561859  0.5913528  
-0.8441891  0.2285653 -0.1231755
  [9]  0.5190459 -0.7803617
 > rnorm(10)
  [1] -0.9585881 -0.0458582  1.1967342  0.6421980 -0.5290280  
-1.0735112  0.6346301  0.2685760
  [9]  1.5767800  1.0864515
 > rnorm(10)
  [1] -0.60400852 -0.06611533  1.00787048  1.48289305  0.54658888  
-0.67630052  0.52664127 -0.36449997
  [9]  0.88039397  0.56929333

I cannot imagine a situation where one would _want_ the output to be  
the same on repeated calls unless one reset a seed. Unless perhaps I  
am not understanding the meaning of "random" in the financial domain?

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Christophe Dutang
    

    

      
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It does not help the problem, but Halton numbers belong to the family  
of quasi random sequence. Yes generally two calls to quasi RNG produce  
the same sequence. They are intended to be well equidistributed but  
not random.

By the way, two to pseudo RNGs produce differents sequences because  
the algo uses the machine time to initiate the seed. Both quasi and  
pseudo RNG are deterministic algo. With Petr Savicky, we make a  
vignette on this topic for randtoolbox.

iPhone.fan

Le 15 sept. 2009 ? 17:37, David Winsemius <dwinsemius at comcast.net> a  
?crit :