NLMIXED in R

NLMIXED Diagnostics

Grass_new<-groupedData(y~x|Trial/Code,
                       data=Grass2,
                       FUN=mean,
                       labels=list(x="Time", y="DMres"))   
try.nlm1<-nlme(y~U+D*exp(-(Kd*x)),
               data=Grass_new,
               fixed=U+D+Kd~1, 
               random=U+D~1|Trial/Code,
               start=c(U=20,D=50.88,Kd=0.02698),
               method="REML", 
               control=nlmeControl(maxIter=1000, msMaxIter = 100))
summary(try.nlm1)
plot(augPred(try.nlm1, level=0:2))
plot(try.nlm1)
plot(ranef(try.nlm1))
fixef(try.nlm1)
qqnorm(try.nlm1)
anova(try.nlm1)
pairs(try.nlm1) # perfect correlations?
plot(Variogram(try.nlm1))
fixed.effects((try.nlm1))
random.effects(try.nlm1)[1] # random effect of Trial for U and D
random.effects(try.nlm1)[2] # random effect of Cow for U and D

plot(acf(resid(try.nlm1))) # for determining an MA aspect
plot(pacf(resid(try.nlm1))) # for determining an AR aspect

try.nlm4RE <- ranef(try.nlm1, aug = TRUE, level=1)
plot(try.nlm4RE, form = ~ Cow)
plot(try.nlm4RE, form = ~ Sample)
try.nlm4RE <- ranef(try.nlm1, aug = TRUE, level=2)
plot(try.nlm4RE, form = ~ Cow)
plot(try.nlm4RE, form = ~ Sample)