Reputation: 606
I have a large number of data points, each with a different associated probability of being 0 or 1. Is there a way in R to create a vector of 0s and 1s sampled from these probabilities? The following code shows how to do what I want, but it's in a loop.
n <- 10
x <- letters[1:n] # my data
p <- runif(n) # my probabilities of the result being 1
result <- numeric()
for(ii in 1:n){
result[ii] <- sample(x = c(0,1), 1, prob = c(1-p[ii], p[ii]))
}
print(cbind(x, p, result))
The result is something like:
x p result
[1,] "a" "0.0407166101504117" "0"
[2,] "b" "0.632280522491783" "1"
[3,] "c" "0.754841333255172" "0"
[4,] "d" "0.0509465073700994" "0"
[5,] "e" "0.629663853673264" "0"
[6,] "f" "0.357108945958316" "0"
[7,] "g" "0.808141406625509" "1"
[8,] "h" "0.671664241468534" "1"
[9,] "i" "0.0218871515244246" "1"
[10,] "j" "0.689538966864347" "1"
Upvotes: 0
Views: 716
Reputation: 156
I'm not sure if I understand correctly, because I get confused by the letters... How about this?
set.seed(1) # reproducibility
n <- 10
p <- runif(n) # probabilities
result <- rbinom(n,1,p)
cbind(p,result)
p result
[1,] 0.26550866 0
[2,] 0.37212390 0
[3,] 0.57285336 0
[4,] 0.90820779 1
[5,] 0.20168193 0
[6,] 0.89838968 1
[7,] 0.94467527 1
[8,] 0.66079779 0
[9,] 0.62911404 1
[10,] 0.06178627 0
Upvotes: 3