Try this:
dat <- data.frame(x=11:14, pa=1:4/10, pb=4:1/10)
f <- function(numreps, data){
pmat <- as.matrix(data[-1])
x <- data[,1]
result <- matrix(0, nrow=numreps, ncol=ncol(pmat))
colnames(result) <- c("A", "B")
for(i in seq_len(numreps)){
result[i,] <- apply(pmat, 2, function(p)
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 con
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 0.20.30.1
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