Is there a way to replicate Excel's goal seek in R involving sumif

Question

I have what I think is a fairly simple ask but I don't seem to be finding a solution for it.

Here's a reproducible example

Cost <- c(100,200,300,400,500)
Savings <- c(10,20,30,40,50)
Fees <- c(20,20,20,20,20)

Data <- data.frame(Cost,Savings,Fees)
ROI <- function(x) {
    sum(subset(Data,Cost>=x)$Savings)/sum(subset(Data,Cost>=x)$Fees)
    }

Basically I want to find the optimum value of the Cost (x) which will make the ROI = 2

In Excel what I do is

Assuming you have Cost, Savings, and Fees in columns A, B, and C respectively.

In cell E2, I wrote the function below

SUMIF($A$2:$A$6,H2,$B$2:$B$6)/SUMIF($A$2:$A$6,H2,$C$2:$C$6)

Where H2 has the following function: CONCATENATE(">",G2)

G2 is the parameter of interest here.

I then go to Data What-If analysis > Goal Seek

Set Cell E2 to Value 2 by changing G2

Is there a way to replicate Excel's steps in R? Thank you!

PS in R, If I did
ROI (201) or ROI (299)
I get 2
What I want to find is the 201.

Answer 1

You could try the uniroot() function to find the value x where your ROI function - 2 ==0.

Cost <- c(100,200,300,400,500)
Savings <- c(10,20,30,40,50)
Fees <- c(20,20,20,20,20)

Data <- data.frame(Cost,Savings,Fees)

ROI <- function(x, targetROI) {
   y<-sum(subset(Data,Cost>=x)$Savings)/sum(subset(Data,Cost>=x)$Fees)
   y-targetROI
}

uniroot(ROI, c(0,500), targetROI=2)

Note Since there is a step change in your function, there are multiple roots this function from x=201 to x=300