Dear Mark,
I would include the repeated measure as the smallest stratum in the random
effects specification:
random=~1|sampleunit/year
Setting up user-defined variance structures should be possible using for
example:
weights=varPower(form=~habitat)
or also try out the available corStruct() classes (found in Pinheiro and Bates
2000)
HTH
Christoph
Mark Na schrieb:
Hello,
We are attempting to use nlme to fit a linear mixed model to explain bird
abundance as a function of habitat:
lme(abundance~habitat-1,data=data,method="ML",random=~1|sampleunit)
The data consist of repeated counts of birds in sample units across multiple
years, and we have two questions:
1) Is it necessary (and, if so, how) to specify the repeated measure
(years)? As written, the above code does not.
2) How can we specify a Toeplitz heterogeneous covariance structure for this
model? We have searched the help file for lme, and the R-help archives, but
cannot find any pertinent information. If that's not possible, can we adapt
an existing covariance structure, and if so how?
Thanks, Mark
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
.
--
Dr. rer.nat. Christoph Scherber
University of Goettingen
DNPW, Agroecology
Waldweg 26
D-37073 Goettingen
Germany
phone +49 (0)551 39 8807
fax +49 (0)551 39 8806
Homepage http://www.gwdg.de/~cscherb1
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
