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.

Attachment: 64bit-halton.ps
Description: PostScript document

Attachment: 32bit-halton.ps
Description: PostScript document


Neither version seemed to change with repeated invocations which I thought odd in what I thought would be graphic realization of random function, but then I don't know much about this area of statistics, so I don't know is the output is supposed to appear deterministic.

Running the suggested replacement causes an error on both 32 bit and 64 bit machines:
> hist(halton(n = 5000, dim = 1, norm=TRUE), main = "Normal Halton",
+ xlab = "x", col = "steelblue3", border = "white")
Error in hist(halton(n = 5000, dim = 1, norm = TRUE), main = "Normal Halton", :
  could not find function "halton"

> sessionInfo()
R version 2.9.1 Patched (2009-07-04 r48897)
x86_64-apple-darwin9.7.0

locale:
en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] fOptions_290.75 fBasics_2100.77 MASS_7.2-47 timeSeries_2100.83 timeDate_290.85
--
David



On Sep 15, 2009, at 1:46 AM, Christophe Dutang wrote:

It does not solve your problem, but in the future, you should use the
halton function, since Diethelm Wuertz and I decided it to move
runif.halton (based on fortran code) to the randtoolbox package. In
the man page, there is an example of plot:

hist(halton(n = 5000, dim = 1, norm=TRUE), main = "Normal Halton",
xlab = "x", col = "steelblue3", border = "white")

But unfortunately, I do not have a 64 bit version of R, so I can not
help you. Let me know if there is a problem with the fortran code.

Christophe

Le 15 sept. 09 à 03:55, Anirban Mukherjee a écrit :

Sorry, but of course.

rnorm.halton should be "almost" identical to rnorm (rnorm gives draws
from a 0 mean, 1sd Normal). Halton sequences (amongst other things)
allow one to draw from the normal in a "more intelligent" fashion when
integrating. Using hist, you should see the classic "bell curve"
centered around 0. Almost identical to

hist(rnorm(1000), plot=TRUE)

The 32 bit "version" gives the bell curve. My 64 bit version gives a
totally different plot (nothing subtle) ... some times with only
positive values for all 100 draws. My 64 bit version of rnorm.halton
also often outputs a bunch of NaNs. If both your plots look like a
bell curve, the problem is on my machine/end.

Thanks very much: do greatly appreciate it.

Best,
Anirban

On Mon, Sep 14, 2009 at 9:31 PM, Steve Lianoglou
<[email protected]> wrote:
Hi,

On Mon, Sep 14, 2009 at 8:28 PM, Anirban Mukherjee <[email protected]

wrote:
To add:

If I try to install using the mac.binary, it tells me (on opening
the
64 bit app) that the package is not installed for x64. And does not
let me load the library when using 64 bit mode. However, if I
install
the package from source, then it installs for x64, but gives me
weird
results.

Again: would appreciate if some one could confirm so that I can
contact the authors and let them know. I do need Halton normals for
some thing I am working on, and I am sitting right on that
borderline
point where the memory constraints of the 32 bit app are making me
lose sleep ...

I wouldn't know what to look for to tell you if it's going wrong or
not.

I have no idea about anything related to financial modeling and don't
have the fOptions package installed anyway.

Perhaps if you post the two images you get:
i. what you expect to see/what you get from 32bit
ii. the wrong image that you're getting from the 64bit version

One of us can confirm/deny that we get the same thing.

Otherwise, I really can't give you an educated answer w/o having to
looking into what this 'halton' stuff is anyway ...

So .. help us help you :-)

I'm not sitting at a 64 bit machine atm, so hopefully someone else
can
help you before I get back to school tomorrow ...

-steve

--
Steve Lianoglou
Graduate Student: Computational Systems Biology
| Memorial Sloan-Kettering Cancer Center
| Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact




--
Anirban Mukherjee | Assistant Professor, Marketing | LKCSB, SMU
5062 School of Business, 50 Stamford Road, Singapore 178899 |
+65-6828-1932

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Christophe Dutang
Ph.D. student at ISFA, Lyon, France
website: http://dutangc.free.fr







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