I have a question related to this one:
Is there a function that allows one to simultaneously estimate a
variance-covariance matrix of the errors for a multiple linear
model? It would be straightforward to do this in two steps,
estimating the covariance matrix using the residuals. But is
there a canned function for a maximum likelihood estimates?
Thanks,
Mike Roberts
>>> Thomas Lumley <tlumley at u.washington.edu> 08/20 1:29 PM
>>>
On Mon, 20 Aug 2001, Pesl Thomas wrote:
> By error I used the function lm with arrays. Is this a legal
action?> funtion call:
> h.lm<-lm(h.0~h.9+h.8)
> where all of the variables are arrays of dimension 722,6,10
>
It's legal, but in this case won't have been what you wanted.
A matrix on the right-hand side of the formula means to use all the
columns of the matrix as predictors. A matrix on the left-hand side
means
a multiple linear model: fitting each column separately as the
response
variable.
-thomas
Thomas Lumley Asst. Professor, Biostatistics
tlumley at u.washington.edu University of Washington, Seattle
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