How to combine two vectors and get all the results of a given account with them

Question

I’m trying to make a calculation, and I need your help. First I make a sequence with normal distribution with 420 numbers, then I make a sequence of numbers I call mci with 42 numbers, then the next calculation has a condition if.

In this part I need that in my condition always compare the first vector list of the mci with the first number of values I generated from my normal distribution, then the whole process is repeated with the second number until the 420 is completed.

For example: For Rp = (28, 27, 26...), bwg = (account with mci[i]) > Rp

I want that rp Always be 28 until you finish the first sequence of 42 numbers, and then compare with 27 of the second sequence of my vector.

Note that the condition always compares the same value of rp, and I think the R is not doing this, comparing for example the value 26.912 with 0.435 where it should compare with the 0.429

max <- 30
K <- 0.0118
Xm <- 21
SD <- 0.851636356306513 
mean.b <- 28

rp <- rnorm(420, mean = mean.b, sd = SD)
BW <- 0.0223*rp^0.8944 
mci <- seq(200, 270, 1.7)
bwg <- ifelse((max*(1-exp(-K*(MCi-(BW*Xm))))) > rp, yes = rp, no = (max*(1-exp(-K*(MCi-(BW*Xm))))))

Answer 1

Well, if I understand your problem correctly, you want to calculate the expression bwg <- (max*(1-exp(-K*(MCi-(BW*Xm))))) for all combinations of mci and rp, and then keep, for each calculated value, the lowest value between rp and the value of bwg obtained.

If that’s the case, you need more than a simple ifelse, because you have two vectors with length > 1 to match. In this case, I decided to make a sapply in the vector rp, and then get the values of bwg for all mci for each rp.

You can also transform the calculation of bwg in a function, not to keep repeating the formula. Finally, I used the function pmin instead of a ifelse, because it looks more elegant.

Follow the code with some comments:

maxVal <- 30 # Mudei o nome desse valor, já existe a função max, melhor não misturar
K <- 0.0118
Xm <- 21
SD <- 0.851636356306513 
mean.b <- 28

rp <- rnorm(420, mean = mean.b, sd = SD)
mci <- seq(200, 270, 1.7)

bwg.calc <- function(maxVal, K, MCi, Xm, rp) {
  BW <- 0.0223*rp^0.8944 # Esse valor depende apenas de rp, pode ser obtido aqui
  maxVal*(1-exp(-K*(MCi-(BW*Xm))))
}       

resultado <- sapply(rp, function(i) { # Para cada rp, calculamos contra todos mci
  bwg <- bwg.calc(maxVal = maxVal, K = K, Xm = Xm, MCi = mci, rp = i)
  pmin(i, bwg) # Poderia ser ifelse(bwg > i, i, bwg)
})

I will not put the result because it is an array with 42 rows (size of Rp and 420 columns (size of mci):

> str(resultado)
 num [1:42, 1:420] 26.8 26.9 27 27 27.1 ...