[R] simulating binary variables

[Jonathan Baron]

On 08/09/02 13:28, laura at bayesian-bay.freeserve.co.uk wrote:

>I am wanting to simulate a data set consisting of a Y variable
 and several X variables, all either binary or discrete. I am
 wondering how to go about doing this and have failed to find
 anything about this in the R -help.

Try runif() in the base package.  It generates random numbers
from a uniform distribution.  So, for example, if you want a
binary variable with an expectation of .75, and 1000
observations, say:

runif(1000)<=.75

Or, if you want to see the numbers right away:

(runif(1000)<=.75)+0

To generate a factor with several levels, you can apply cut() to
runif().  That may be sufficient, but note that factors are
"categorical variables."

Of course, you assign these to variables, e.g.,

x1 <- runif(1000)<=.75

and then use these in your model.

Jon
-- 
Jonathan Baron, Professor of Psychology, University of Pennsylvania
Home page:            http://www.sas.upenn.edu/~baron
Questionnaires:       http://www.psych.upenn.edu/~baron/qs.html
Psychology webmaster: http://www.psych.upenn.edu/
R page:               http://finzi.psych.upenn.edu/
-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
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
_._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._