[R] extracting estimated covariance parameters from lme fit

[Green, Gerwyn (greeng6)]

Dear all

Apologies in advance as this seems like a trivial question. Nonetheless,
a question I haven't been able to resolve myself !. Within a single
repetition of a simulation (to be repeated many times) I am fitting the
following linear mixed model using lme...

Y_{gtr} = \mu + U_{g} +  W_{gt} + Z_{gtr}

U_{g} ~ N(0,\gamma^{2}), W_{gt} ~ N(0,\kappa^{2}), Z_{gtr} ~
N(0,\tau^{2})

g = 1,...,G
t = 1,...,T
r= 1,...,R


...by doing

> Model.fit <- lme(Y ~ 1, data=data, random= ~1|gene/treatment)

I would like to be able to extract the estimated covariance parameters
contained within the lme object. I know if I type...

> Model.fit$sigma


...then I get the estimated residual variance, i.e. within the context
of the above model, the estimate for \tau. But I would also like to
extract the estimates for \gamma and \kappa by doing
Model.fit$"something". I am aware that I can view the output using the
extractor function "summary", but within a single repetition of my
simulation routine I want to be able to code something like

gamma <- Model.fit$..... 
kappa <- Model.fit$.....


and then plug `gamma' and `kappa' into some formulae. This process of
fitting and extracting will be repeated many times, which is why I wish
to automate everything.

Again, any help would be greatly appreciated

Best

Gerwyn Green
School of Health and Medicine
Lancaster University






Any help would be greatly appreciated

Best


Gerwyn Green
School of Health and Medicine
Lancaster Uinversity