creating functions to calculate the technical error and the coefficient of variation of the error - r

Question

I have this equation (which can be accessed through this link):
I would like to create two functions by using r. The first one is by using the first equation provided.
The second function is to create a mathematical formula in which the first function is substituted. Here is the formula:
(http://i43.tinypic.com/b6vq5j.jpg)
THis is the head of my data: (data_1)
sex age seca1 chad1 DL alog1 dig1 scifirst1 crimetech1
1 F 20 1754 1750 175 95 95 432 429
2 F 19 1594 1596 158 56 55 420 417
3 F 20 1556 1558 156 74 72 435 437
4 F 18 1648 1640 167 67 65 431 434
5 F 19 1780 1780 178 99 67 433 431
6 F 19 1610 1620 165 56 54 423 425
After doing this as #janos suggested:
f1 <- function(x, y) {sqrt(sum((x - y) ^ 2) / 2 / length(x))}
now, as i need to run f1 on data_1$alog1 vs data_1$dig1... here's what i did:
f1(data_1$alog1, data_1$dig1)
which gives: 4.3
Next, I tried to implement the 2nd formula like this:
f2 <- function(x, y){(f1 / ((x + y) / 2)) * 100}
but then, when I run it on data_1$alog1 vs data_1$dig1 to calculate the coefficient of variation of the error for these data I get:
> f2(data_1$alog1, data_1$dig1)
Error in f1/((x + y)/2) : non-numeric argument to binary operator
Could anyone please comment on the steps performed to create the first function, the second function and the way i run the functions on "alog1 vs dig1" ?
Thanks all!!

Answer 1

If I understood correctly, here you go:
f1 <- function(x, y) {
sqrt(sum((x - y) ^ 2) / 2 / length(x))
}
f1(1:3, 4:6)
This will output:
[1] 2.12132
The function assumes that x and y are both vectors of the same length.
You can do the same for the 2nd function, with some simplification:
f2 <- function(x, y) {
200 * f1(x, y) / (x + y)
}
f2(1:3, 3:5)
To check that two vectors have the same length, you can use the length method. It can be also useful to halt execution if this assumption fails, like this:
stopifnot(length(x) == length(y))