Dear all,
I am dealing with a nonlinear model of the form yt = A*exp(-B*T)*Yt-1, where T
represents time and Yt-1 accounts for the accumulated values of y from T=0 to
t-1.
The problem of the models is that the error terms are autocorrelated, so I have
to deal with a model combining
Dear all,
I am fitting a nonlinear mixed-effects model from a balanced panel of data
using nlme. I would like to know whay would be the best options for formally
testing for autocorrelation. Is it possible to carry out a Durbin-Watson test
on a nlme object? As far as I've seen, I think the
Dear all,
I am fitting a nonlinear mixed-effects model from a balanced panel of data
using nlme. I would like to know whay would be the best options for formally
testing for autocorrelation. Is it possible to carry out a Durbin-Watson test
on a nlme object? As far as I've seen, I think the
Dear all,
I am trying to fit a nonlinear model with a autocorrelation term, but everytime
I type in the command, I got an error message from Winwows and R closes itself.
The command line is as follows:
mod1-nlme(V~A*exp(-B*A.O)*Vac.t.1.,data,fixed=A+B~1,random=A+B~1|ORDINAL,+
Dear all,
I am trying to fit a mixed-effects non linear regression, but I have some
trouble with it. My data are a balanced panel of 904 subjects with 8
observations (at regular periods) per subject.
The functional form of my model is Y=Aexp(-BX1)X2 +e. I want to allow
parameters A and B to
