Spencer,
I tried the mixed effects approach you suggest using the random effects
module of
AD Model Builder: (http://www.otter-rsch.ca/admbre/admbre.html). What are
94 unbounded parameters in Schnute et al (1998), now become realizations
of a Gaussian random variable, with the corresponding
Douglas Bates wrote:
snip
Don't you find it somewhat disingenuous that you publish a comparison
between the AD Model Builder software that you sell and R - a
comparison that shows a tremendous advantage for your software - and
then you write I am not proficient in R?
I think there is
On 11/24/06, dave fournier [EMAIL PROTECTED] wrote:
Dave
Did you try supplying gradient information to nlminb? (I note that
nlminb is used for the optimization, but I don't see any gradient
information supplied to it.) I would suspect that supplying gradient
information would
There has recently been some discussion on the list about
AD Model builder and the suitability of R for constructing the
types of models used in fisheries management.
https://stat.ethz.ch/pipermail/r-help/2006-January/086841.html
dave fournier [EMAIL PROTECTED] wrote:
I think that many R users understimate the numerical challenges
that some of the typical nonlinear statistical model used in different
fields present. R may not be a suitable platform for development for
such models.
Around 10 years ago John Schnute,
Did you try supplying gradient information to nlminb? (I note that
nlminb is used for the optimization, but I don't see any gradient
information supplied to it.) I would suspect that supplying gradient
information would greatly speed up the computation (as you note in
comments at
Dave
Did you try supplying gradient information to nlminb? (I note that
nlminb is used for the optimization, but I don't see any gradient
information supplied to it.) I would suspect that supplying gradient
information would greatly speed up the computation (as you note in
comments
Hi, Mike Dave:
Have you considered nonlinear mixed effects models for the types
of problems considered in the comparison paper you cite? Those
benchmark trials consider T years of data ... for A age classes and
the total number of parameters is m = T+A+5. Without knowing more
about
