Hi,
Suppose I want to test a set of random numbers (using the Binormal random
number generator), input the following command to generate a set of random
numbers:
test <- rbinom( 10000000, 1, 0.5 )
How can I, after obtaining the result, export the vector "test" into an text
file?
Then, suppose I want to do something like:
> x <- 1e10
> x
[1] 1e+10
> test <- rbinom( x, 1, 0.5 )
Error in rbinom(n, size, prob) : invalid arguments
Why would I get the error message given that x is a number?
Thanks,
Kevin
-------------------------------------------------
Ko-Kang Kevin Wang
Statistical Analysis Division Leader
Software Developers' Klub
University of Auckland
New Zealand
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Random Number Testing...
2 messages · Ko-Kang Kevin Wang, Brian Ripley
On Sun, 8 Apr 2001 Ko-Kang at xtra.co.nz wrote:
Hi,
Suppose I want to test a set of random numbers (using the Binormal random
number generator), input the following command to generate a set of random
numbers:
test <- rbinom( 10000000, 1, 0.5 )
How can I, after obtaining the result, export the vector "test" into an text
file?
?write or see the R Data Import/Export manual. Do do this in smaller pieces, though, using connections to keep the file open.
Then, suppose I want to do something like:
> x <- 1e10
> x
[1] 1e+10
> test <- rbinom( x, 1, 0.5 )
Error in rbinom(n, size, prob) : invalid arguments Why would I get the error message given that x is a number?
Assuming you have a 32-bit machine, you can't allocate storage for 10 billion random numbers, and I think you also have an integer overflow problem (10 billion is bigger than 2^32). In either case, n is invalid. I don't get that error message but
test <- rbinom( x, 1, 0.5 )
Error: cannot allocate vector of size 4194303 Kb on Solaris. On i686 Linux I get what you reported. Probably asInteger behaves differently, as it just takes (int) on a double, and I don't think the behaviour of that when the double is out of range is prescribed in the C standard. Finally, if you could get 10billion numbers out, testing them is not really fair as that's far more than one could reasonably use in an R simulation. (Quick sanity check: they would take a week or so just to generate on a 1GHz machine.)
Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272860 (secr) Oxford OX1 3TG, UK Fax: +44 1865 272595 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._