Hello,
is there a way to compute multilevel (3-stage) regression using weights
matrix (on different levels, just like in HLM) in R ? The nlme package
doesn't seem to get the job done. Do you have any suggestions ? I _really_
don't want to use HLM to do this.
Best,
MikoÅaj Hnatiuk
2012/11/29 Greg
The gls function in the nlme package is one approach.
If you know the covariance matrix exactly (it is just numerical with
nothing that needs to be estimated) then you can also take the Cholesky
decomposition of the inverse of the covariance matrix (or other square root
method) and multiply the x
Hi all,
I would
like to do a weighted linear regression, when the error of the dependent
variable
is correlated. So I have a weighting (covariance) matrix instead of a vector. As
I understood the weights argument in the lm function should be a vector and
not a matrix. Can anyone suggest m
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