Message-ID: <1458735896.636716.1308619145729.JavaMail.root@jaguar7.sfu.ca>
Date: 2011-06-21T01:19:05Z
From: Rian Dickson
Subject: Coefficient matrix not invertible
In-Reply-To: <1240186825.636512.1308618591478.JavaMail.root@jaguar7.sfu.ca>
hello again,
Thanks for the recent answers to my other questions - they've been quite useful.
I've run into another problem a little further along.
When I try to run this model:
global.ri.vf1.cs1.lme <- lme(Log.minH ~ site + f.year + cohort + emerg + emergSQ + pri + priSQ
+ start.t + startSQ + sea + tidem + tided, data = SUSCforage, random = ~1|scoterID,
weights = varExp(form =~Log.minH), correlation = corAR1(form =~ Date|scoterID), method = "REML")
I get this error message:
Error in `coef<-.corARMA`(`*tmp*`, value = 20.3619280472088) :
Coefficient matrix not invertible
However, if I try the same model except without the variance weighting, it works fine.
Also, with the variance weighting included,
corARMA(form =~ Date|scoterID, p=0, q=1) works
but
corARMA(form =~ Date|scoterID, p=1, q=1) returns a similar error message as above.
Error in `coef<-.corARMA`(`*tmp*`, value = c(21.0236910353017, -6.13825550757903 :
Coefficient matrix not invertible
I'm not sure what this means, or if there is anything I can do about it.
Any advice would be appreciated.
thank you,
Rian
*************************************
Rian Dickson
M.Sc. candidate
Centre for Wildlife Ecology
Department of Biological Sciences
Simon Fraser University
8888 University Drive
Burnaby BC V5A 1S6
778.782.5618