Reputation: 4602
i have a problem doing the linear regression with three Matrix objects.
m1 = matrix(c(1:10))
m2 = matrix(c(10:19))
m3 = matrix(c(100:109))
I DO NOT have problem if i do:
mod = lm(m1+m2 ~ m3+0)
I have the problem if i only use TWO Matrixs, like:
m1 = matrix(c(1:20), ncol=2)
m2 = matrix(c(1:10))
mod = lm(m1 ~ m2+0)
in this case i get TWO coefficients for m2:
Coefficients:
[,1] [,2]
m2 1.000 2.429
but I do not want it I would like that the two columns of the m1 matrix will be as the previous example (like two distinct columns)
How to do it?
Upvotes: 1
Views: 8986
Reputation: 4795
In your first example you are summing your two column vectors row-wise together and using that as the target. For the matrix m1 I think you want the rowsums as the predictor.
like:
m1 = matrix(c(1:2000), ncol=200)
m2 = matrix(c(1:10))
msum=apply(m1,1,sum)
now use msum for your response.
mod = lm(msum ~ m2+0)
This gives just one coeficient. I think this is what you want, but I am still not sure why you would want this?
Upvotes: 2