I have 365 columns. In each column I have 60 values. I need to know the rate of change over time for each column (slope or linear coefficient). I created a generic column as
Here's a way to do it:
# Fake data
dat = data.frame(x=1:60, y1=rnorm(60), y2=rnorm(60),
y3=rnorm(60))
t(sapply(names(dat)[-1], function(var){
coef(lm(dat[,var] ~ x, data=dat))
}))
(Intercept) x
y1 0.10858554 -0.004235449
y2 -0.02766542 0.005364577
y3 0.20283168 -0.008160786
Now, where's that turpentine soap?