
Hi there fellow R-users, 

I am trying to follow an example of modelling a serial correlation structure
in the textbook "Mixed Effects Model in S and Splus". 
However, I am getting some very odd results. Here is what I am trying to
run: 


library(nlme)
data(Ovary)
fm1<-lme(follicles~sin(2*pi*Time)+cos(2*pi*Time),data=Ovary,random=pdDiag(~s
in(2*pi*Time)))

### The example is fine up to here with all parameter estimates being
identical to that in the book. 


fm2<-update(fm1,correlation=corAR1())

#### The parameters of fm2 are different to that in the book and 

plot(ACF(fm2))

##### signifies that serial correlation still exists in the residuals.




###### When I try and run this (which runs fine in the book)

fm5<-update(fm1,corr=corARMA(p=1,q=1))

#### I get the following error message 

#Error in "coef<-.corARMA"(*tmp*, value = c(62.3428455941166,
62.3428517930051 : 
#       Coefficient matrix not invertible


I have tried running the example on R for windows versions 1.7.1 and 1.8.1
with the same results. 

Can anyone shed light on this?? Perhaps another R-user could kindly run this
example and see if they get the same results??

Kind regards,

Wayne


Dr Wayne R. Jones
Senior Statistician / Research Analyst
KSS Limited
St James's Buildings
79 Oxford Street
Manchester M1 6SS
Tel: +44(0)161 609 4084
Mob: +44(0)7810 523 713




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