[R-SIG-Mac] rnorm.halton

[Christophe Dutang]

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 à 17:37, David Winsemius <dwinsemius at comcast.net> a  
écrit :

>
> On Sep 15, 2009, at 11:10 AM, Anirban Mukherjee wrote:
>
>> Thanks everyone for your replies. Particularly David.
>>
>> The numbers are pseudo-random. Repeated calls should/would give the
>> same output.
>
> 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?
>
> -- 
> David
>
>> 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:
>>> I get very different output from the two versions of Mac OSX R as
>>> well. The 32 bit version puts out a histogram that has an expected,
>>> almost symmetric unimodal distribution. The 64 bit version created a
>>> bimodal distribution with one large mode near 0 and another smaller
>>> mode near 10E+37. Postcript output attached.
>>>
>>
>>
>>
>> -- 
>> Anirban Mukherjee | Assistant Professor, Marketing | LKCSB, SMU
>> 5062 School of Business, 50 Stamford Road, Singapore 178899 | +65-6828-1932
>>
>> _______________________________________________
>> R-SIG-Mac mailing list
>> R-SIG-Mac at stat.math.ethz.ch
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mac
>
> David Winsemius, MD
> Heritage Laboratories
> West Hartford, CT
>
> _______________________________________________
> R-SIG-Mac mailing list
> R-SIG-Mac at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/r-sig-mac