If the trials are not connected then I would consider melting the table
using melt() from the reshape package.
And then using lapply() with the function
random.function <- function(my.prob, number.of.observations = 10)
{
sum(rbinom(number.of.observations, 1, my.prob))
}


in case the trials are connected, by column,
than you could use
apply(the.data.table, 2, a.function)
on it. Where "a.function" will to multinum distribution (for which I don't
remember the function at the moment, but it can be searched).


Best,
Tal.




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On Wed, Jan 13, 2010 at 7:20 PM, Kelvin <6kelvin6@gmail.com> wrote:

> Dear friends,
>
> If I have a table like this, first row A B C D ... are different
> levels of the variable, first column 0 1 2 4 ... are the levels of the
> "numbers", the numbers inside the table are the probabilities of the
> "number" occuring.
>
>    A      B      C       D    ...
> 0  0.2    0.3    0.1    0.05
> 1  0.1    0.1    0.2    0.2
> 2  0.02  0.2    0       0.1
> 4  0.3    0.01  0.01   0.4
> ...
>
> How can I use R to do the simulation and get a table like this, first
> row A B C D ... are different levels of the variable, the numbers
> inside the table are the "numbers" simulated from the probailties
> table above?
>
>    A  B  C  D ...
>    0  4   2   0
>    2   2  0   1
>    0   1  4   1
>    2   2  0   0
>    ...
>
>
>    Thanks for help!
>
>
>    Kelvin
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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