For loops for nested variables within function in R - r

Question

I would like to iterate through vectors of values and calculate something for every value while being within a function environment in R. For example:
# I have costs for 3 companies
c <- c(10, 20, 30)
# I have the same revenue across all 3
r <- 100
# I want to obtain the profits for all 3 within one variable
result <- list()
# I could do this in a for loop
for(i in 1:3){
result[i] <- r - c[i]
}
Now lets assume I have a model that is very long and I define everything as a function which is to be solved with various random draws for the costs.
# Random draws
n <- 1000
r <- rnorm(n, mean = 100, sd = 10)
c1 <- rnorm(n, mean = 10, sd = 1)
c2 <- rnorm(n, mean = 20, sd = 2)
c3 <- rnorm(n, mean = 30, sd = 3)
X <- data.frame(r, c1, c2, c3)
fun <- function(x){
r <- x[1]
c <- c(x[2], x[3], x[4])
for(i in 1:3){
result[i] <- r - c[i]
}
return(result)
}
I could then evaluate the result for all draws by iterating through the rows of randomly sampled input data.
for(j in 1:n){
x <- X[j,]
y <- fun(x)
}
In this example, the output variable y would entail the nested result variable which comprises of the results for all 3 companies. However, my line of thinking results in an error and I think it has to do with the fact that I try to return a nested variable? Hence my question how you guys would approach something like this.

Answer 1

I would suggest rethinking your coding approach. This is a very un-R-like way of doing things.
For example, the first for loop can be written much more succinctly as
x <- c(10, 20, 30)
r <- 100
result <- lapply(-x, `+`, r)
Then fun becomes something like
fun <- function(x) lapply(-x[-1], `+`, x[1])
To then operate over the rows of a data.frame (which is what you seem to do in the last step), you can use something like
apply(X, 1, fun)
where the MARGIN = 1 argument in apply ensures that you are applying a function per row (as opposed to per column).

Answer 2

Here's an approach using your function and a for loop:
# Random draws
n <- 1000
r <- rnorm(n, mean = 100, sd = 10)
c1 <- rnorm(n, mean = 10, sd = 1)
c2 <- rnorm(n, mean = 20, sd = 2)
c3 <- rnorm(n, mean = 30, sd = 3)
X <- data.frame(r, c1, c2, c3)
result <- list()
fun <- function(x){
r <- x[[1]]
c <- c(x[[2]], x[[3]], x[[4]])
for(i in 1:3){
result[i] <- r - c[i]
}
return(result)
}
# Create a list to store results
profits <- rep(rep(list(1:3)),nrow(X))
# Loop throuhg each row of dataframe and store in profits.
for(i in 1:nrow(X)){
profits_temp <-
fun(list(X[i,"r"],X[i,"c1"],X[i,"c2"],X[i,"c3"]))
for(j in 1:3)
profits[[i]][[j]] <- profits_temp[[j]]
}
# Eye results
profits[[1]]
#> [1] 93.23594 81.25731 70.27699
profits[[2]]
#> [1] 80.50516 69.27517 63.36439