Odtnhj

I'm trying to create a function that simulate dolling m dice, n times, calculate the minimum of the outcome of the dice in each roll and then calculate the mean of the minimum and store the values into a vector.

mindice = function(n = 10, m = 3)

 v <- vector
 for(i in 1:10)
 
 minima= numeric(n)
 for(i in 1:n)
 
 minima[i] = min(sample(6,m,replace=T))
 
 v[i] = mean(minima)
 
v

I'm calling the function like that: mindice()
and the output is: Error in v[i] <- mean(minima) : object of type 'closure' is not subsettable

any help will be appreciated

I don't know if this fits your expectations. This function returns both the vector for the minimum per roll and their average

mindice <- function(n = 10, m = 3)
 
 minima <- vector("numeric")
 for(i in 1:n)
 minima = c(minima, min(sample(6,m,replace=T)))
 
 list(minimum_values=minima,
 mean_minima=mean(minima))
 
mindice()

The comment about using v = vector() rather than v = vector should solve the bug in the way you've written the function. If you're interested in a more R-like way to do this function, try this:

mindice2 = function(n = 10, m = 3) 
 rolls = sample(6, size = m * n, replace = TRUE)
 rolls = matrix(rolls, nrow = m)
 minima = apply(rolls, MARGIN = 2, FUN = min)
 cum_mean = cumsum(minima) / seq_along(minima)
 return(cum_mean)

Rather than sampling each roll separately, we do all the rolls at once (more efficient), and then put them in a matrix where each column is a roll of m dice. We can then use apply to find the minima, and cumsum to calculate the mean minimum after each roll.