Dear all,
As far as I managed to see the weights parameter in nlme::lme(), mgcv::gamm(), gamm4::gamm4(), can be used to pass some specific residual variance structure based on nlme's varFunc class. I was wondering if the following variance structure is possible to be obtained from the already implemented instances in varClasses, or I will need to code it myself.
I want the variance of the response for observation i to be of the form v_i^2 = s^2 + s_i^2, where s^2 is a common for all observations unknown variability and s_i^2 is known, individual specific measurement error variance (can be 0).
Thank you
Best wishes
Krzysztof Bartoszek
Sent with ProtonMail Secure Email.