I have coded the following in R: User chooses a file that contains 2 columns (V1 and V2), with numerous rows (number of rows will vary depending on input file) The script calculates the rsq of the relationship between 2 the variables. There can be anything from 10 to 1000 rows of data depending on the input file.
I want to code the following: The code should loop through all rows, removing/omitting/ignoring one row at a time and calculating the new rsq with this row missing. So, for example:
There are 10 rows of data and the total rsq = 0.97
Step1: The first row of data are removed from the equation
The rsq is calculated again, but this time for 9 rows, giving rsq = 0.98.
Step 2:The 1st row is re-added and the 2nd row is removed
rsq is calculated again
Step 3: The second row is re-added and the 3rd row is removed
rsq is calculated again
After each loop the "new rsq" will be placed in a new column next to the row that was removed.
Can anyone advise how to do this? I have this coded in excel and it works well but is cumbersome and therefore not ideal.
Do you want to do something like this?
# Make some sample data
set.seed(1095)
data <- data.frame( V1 = 1:10 , V2 = sample.int(5 ,10 ,repl = TRUE ) )
# Use sapply to get r2 removing each row at a time
r2 <- sapply( 1:nrow(data) , function(x) ( cor( data[-x,1] , data[-x,2] ) )^2 )
# Combine into a data frame
newdata <- cbind( data , r2 )
newdata
# V1 V2 r2
# 1 1 5 0.2526316
# 2 2 3 0.4657601
# 3 3 5 0.3204721
# 4 4 5 0.3691612
# 5 5 1 0.5405405
# 6 6 3 0.3769480
# 7 7 3 0.3840426
# 8 8 2 0.3409425
# 9 9 1 0.2725806
# 10 10 3 0.4986702