[R] user defined covariance structure

[Jonathan Smith]

I am writing as I am still having trouble trying to define my own covariance 
matrix.  My code is displayed below.  I am defining the covariance matrix in 
the form of an AR1 process so it can be easily checked if working correctly. 
  Another question I have is if it is possible to define the matrix without 
giving p a specific value and leaving it in as a coefficient.  For the 
reason that it can be estimated when model is run.  I figure that is the way 
AR1 works in GLS.
Thank you
Jon Smith
I would appreciate any help s I am stuck here and need to figure this out 
prior to continuing my research.

function ()
{
library(nlme)

tim<-c(1,2,3,4,1,2,3,4,1,2,3,4,1,2,3,4)
peep<-c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4)
y<-c(11.78,9.53,11.03,9.89,10.80,8.74,10.25,10.69,5.60,7.27,6.81,4.56,7.01,5.64,6.30,8.31)
#This y data was created from and AR1 model with correlation coefficient 
equaling 0.7.

timMat<-matrix(c(tim),ncol=1,nrow=16)
peepMat<-matrix(c(peep),ncol=1,nrow=16)
yMat<-matrix(c(y),ncol=1,nrow=16)
dataframe<-data.frame(yMat,timMat,peepMat)
p=0.7
g=1

tester2<-corSymm(value = c(p^(1),p^(2),p^(3),p^(1),p^(2),p^(1)),form = ~ 
timMat|peepMat)
tester2<-Initialize(tester2, data = dataframe)
testMat2<-corMatrix(tester2)
print(testMat2)
# this appears to be working correctly

#smanGls<-gls(yMat~timMat,data = dataframe, corr = corAR1(form = 
~timMat|peepMat))
#		works perfectly

smanGls<-gls(yMat~timMat,data = dataframe, corr = corSymm(tester2))

arsum<-summary(smanGls)
print(arsum)

#this is what message I get when I try to use the covarince matrix I 
defined.
#Error in gls(yMat ~ timMat, data = dataframe, corr = corSymm(tester2)) :
  #      false convergence (8)

}