CODEWITHSUNDEEP
rrandom
Numidian
Numidian

Reputation: 13

Variable sample upper value in R

I have the following matrix

m <- matrix(c(2, 4, 3, 5, 1, 5, 7, 9, 3, 7), nrow=5, ncol=2,) 
colnames(x) = c("Y","Z")
m <-data.frame(m)

I am trying to create a random number in each row where the upper limit is a number based on a variable value (in this case 1*Y based on each row's value for for Z)

I currently have:

 samp<-function(x){
    sample(0:1,1,replace = TRUE)}

    x$randoms <- apply(m,1,samp)

which work works well applying the sample function independently to each row, but I always get an error when I try to alter the x in sample. I thought I could do something like this:

samp<-function(x){
        sample(0:m$Z,1,replace = TRUE)}

        x$randoms <- apply(m,1,samp)

but I guess that was wishful thinking.

Ultimately I want the result:

 Y Z randoms
 2 5       4
 4 7       7
 3 9       3
 5 3       1
 1 7       6

Any ideas?

Upvotes: 0

Views: 111

Answers (2)

Numidian
Numidian

Reputation: 13

Based on @mathematical.coffee suggestion and my edited example this is the slick final result:

m <- matrix(c(2, 4, 3, 5, 1, 5, 7, 9, 3, 7), nrow=5, ncol=2,) 
 colnames(m) = c("Y","Z")
m <-data.frame(m) 

samp<-function(x){
sample(Z + 1, 1)}

m$randoms <- sapply(m$Z + 1, sample, 1) - 1

Upvotes: 1

mathematical.coffee
mathematical.coffee

Reputation: 56915

The following will sample from 0 to x$Y for each row, and store the result in randoms:

x$randoms <- sapply(x$Y + 1, sample, 1) - 1

Explanation:

The sapply takes each value in x$Y separately (let's call this y), and calls sample(y + 1, 1) on it.

Note that (e.g.) sample(y+1, 1) will sample 1 random integer from the range 1:(y+1). Since you want a number from 0 to y rather than 1 to y + 1, we subtract 1 at the end.

Also, just pointing out - no need for replace=T here because you are only sampling one value anyway, so it doesn't matter whether it gets replaced or not.

Upvotes: 1

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