On Wed, 3 Dec 2008, Thomas Petzoldt wrote:
Dear R developers,
I tried to use nlminb instead of optim for a current problem (fitting
parameters of a differential equation model). The PORT algorithm converged
much better than any of optim's methods and the identified parameters are
plausible. However, it took me a while before spotting the reason of a
technical problem that nlminb, in contrast to optim, does not pass names of
the start parameters to the objective function.
Please find below a minimum reproducible example. There is, of course, a
workaround, but in order to make optim and nlme more compatible I would ask
whether it would be possible to change this idiosyncratic behavior?
The 'idiosyncratic behavior' is to expect that a new vector of parameters
will magically inherit names from the start vector. optim() was changed
(and documented) because some users asked for this, and if a user who
wants it for nlminb provides a tested patch, I am sure it will be
considered.
Note the documentation difference.
Tested with:
R version 2.8.0 Patched (2008-11-04 r46830) i386-pc-mingw32
and also
R version 2.9.0 Under development (unstable) (2008-12-03 r47039)
i386-pc-mingw32
Thanks a lot
Thomas Petzoldt
set.seed(3577) # make it reproducible
## 1) example taken from ?nlminb -------------------------------------
x <- rnbinom(100, mu = 10, size = 10)
hdev <- function(par) {
-sum(dnbinom(x, mu = par[1], size = par[2], log = TRUE))
}
nlminb(c(20, 20), hdev, lower = 0.001, upper = Inf)
## --> works without problems
## 2) same example, but with named vectors -----------------------------
hdev <- function(par) {
cat(names(par), "\n") # show what happens
-sum(dnbinom(x, mu = par["mu"], size = par["size"], log = TRUE))
}
start <- c(mu=20, size=20)
optim(start, hdev, lower = 0.001, upper = Inf, method="L-BFGS-B")
## --> works without problems
## 3) THE PROBLEM
nlminb(start, hdev, lower = 0.001, upper = Inf)
## --> $objective is NA because names of "start" are not passed through
## 4) workaround -------------------------------------------------------
hdev <- function(par, pnames) {
names(par) <- pnames
-sum(dnbinom(x, mu = par["mu"], size = par["size"], log = TRUE))
}
nlminb(start, hdev, pnames = names(start), lower = 0.001, upper = Inf)
## --> works, but is it possible to improve nlminb
## so that the workaround can be avoided ?
--
Thomas Petzoldt
Technische Universitaet Dresden
Institut fuer Hydrobiologie [EMAIL PROTECTED]
01062 Dresden http://tu-dresden.de/hydrobiologie/
GERMANY
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--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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