Hello All,
I need to calculate a column (Vupper) using a formula, but I am not sure 
how to. It will be easier to explain with an example. 

Again this is my dataset:
dput(nd)
structure(list(week = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 
29, 30), value = c(9.45, 7.99, 9.29, 11.66, 12.16, 10.18, 8.04, 
11.46, 9.2, 10.34, 9.03, 11.47, 10.51, 9.4, 10.08, 9.37, 10.62, 
10.31, 10, 13, 10.9, 9.33, 12.29, 11.5, 10.6, 11.08, 10.38, 11.62, 
11.31, 10.52), cusum = c(-0.550000000000001, -2.56, -3.27, -1.61, 
0.549999999999999, 0.729999999999999, -1.23, 0.229999999999999, 
-0.570000000000002, -0.230000000000002, -1.2, 0.269999999999998, 
0.779999999999998, 0.179999999999998, 0.259999999999998, 
-0.370000000000003, 
0.249999999999996, 0.559999999999997, 0.559999999999997, 3.56, 
4.46, 3.79, 6.08, 7.58, 8.18, 9.26, 9.64, 11.26, 12.57, 13.09
)), .Names = c("week", "value", "cusum"), row.names = c(NA, -30L
), class = "data.frame")

I have some constants in my data. These are:
sigma =1, h = 5, k = 0.5

The formula requires me to start from the bottom row (30th in this case). 
The formula for the last row will be row 30th Cusi value (13.09) + h(5) * 
sigma(1) = giving me the value of 18.1

Then the formula for the 29th row for Vupper uses the value of 30th Vupper 
(18.1) + k(0.5) * sigma(1) = giving me the value of 18.6

Similarly the formula for the 28th row for Vupper will use value of 29th 
Vupper(18.6) + k(0.5) * sigma(1) = giving me the value of 19.1

And so on?.

Also, is there any way to make the formula generalised using loop or 
functions? Because I really don?t want to have to re-write the program if 
my number of rows increase or decrease or if I use another dataset? 

So far my function looks like following (Without the Vupper formula in 
there):
vmask2 <- function(data,target,sigma,h,k){
  data$deviation <- data$value - target
  data$cusums <- cumsum(data$deviation)
  data$ma <- c(NA,abs(diff(data$value)))
  data$Vupper <- *not sure what to put here*

  data
}
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