glm with four variables
On Fri, 8 Feb 2002, iago mosqueira wrote:
Hi, Yes, it appears R thinks that is the case. lm() complains of singularities.
Ah well, since you are fitting a linear model why not use lm?
I have a total of four variables (dep,lat,ne and date) and Matlab tells me none of them is singular, and the rank of the combined matrix is 4, so they don't appear to be correlated. Is there any way I can avoid this? Or does it simply indicate two variables will be enough here?
You only used three variables (despite your subject), and it's the design matrix that is singular. That has a constant column and expands out any factors. R has an alias function to show you what is aliased in a linear model. I suggest you take some advice on regression from a local expert.
Thanks iago ----- Original Message ----- From: "Martyn Plummer" <plummer at iarc.fr> To: "iago mosqueira" <i.mosqueira at ic.ac.uk> Cc: "R-help" <r-help at stat.math.ethz.ch> Sent: 08 February 2002 13:13 Subject: RE: [R] glm with four variables
On 08-Feb-2002 iago mosqueira wrote:
Hi, Sorry if this is a very basic question, but when I run this glm(formula = loge ~ lat + ne + dep, family = gaussian) summary shows the same formula but results only for the first two
variables.
What am I doing wrong?
Probably dep is aliased: i.e. some linear combination of lat, ne and the intercept equals dep for all values. A model with all four terms is, in this case, unidentifiable so dep is dropped. This appears to take place silently. It might be more useful to issue a warning. Martyn
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