Hi,
I would like to fit lm-models to a matrix with 'samples' of a dependent
variable (each row represents one sample of the dependent variable).
The independent variable is a vector that stays the same:
y <- c(1:10)
x <- matrix(rnorm(5*10,0,1), 5, 10)
now I would like to avoid looping over the rows, since my original matrix is
much larger;
for(t in 1:dim(x)[1]) {
print(lm(y ~ x[t,]))
}
Is there a time-efficient way to do this?
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