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get_msr
2012 Feb 23
1
Improving performance of split-apply problem
...MSE's. Now, regardless of the size of the group, the regression needs
to be run on exactly 40 observations. If the group has less than 40
observations, then I need to add rows to get to 40, populating all
variables with 0's for those extra rows. Here's the function I wrote to do
this:
get_MSE = function(x) {
rownames(x) = x$ID #'ID' can take on any value from 1 to 40.
x = x[as.character(1:40), ]
x[is.na(x)] = 0
regressionResult = lm(A ~ B + C + D + E, data=x) #A-E are some variables
in the data frame.
MSE = mean((regressionResult$fitted.values - A)^2)
return(MSE)
}...