[R] typsize and fscale arguments to nlm
John Fox
jfox at mcmaster.ca
Tue Jul 23 00:43:12 CEST 2002
Dear R list members,
I have a question about the proper use of the typsize and fscale arguments
to nlm.
I use nlm in my sem package to fit general structural-equation models,
which entails maximizing a multinormal likelihood with respect to
parameters that represent regression coefficients and covariances of
variables. The magnitudes of these parameters can be very different.
The documentation for typsize is rather terse: "an estimate of the size of
each parameter at the minimum," with the default typsize=rep(1, length(p))
[where length(p) gives the number of parameters]. Am I correct in
interpreting the "size of each parameter" as its absolute values? If so, is
it reasonable to specify typsize=abs(start), where start contains that
start values of the parameters? I can compute start values that have
generally reasonable magnitudes (certainly more generally reasonable than
assuming that all parameters are of the same magnitude) and that will never
be identically 0. A related question is whether typsize specifies the
relative or absolute "sizes" of the parameters.
Finally, there is another argument to nlm called fscale which specifies "an
estimate of the size of f at the minimum" (where f is the function to be
minimized -- in my case the negative log-likelihood). The default is
fscale=1. In experimenting with nlm I've found that using
typsize=abs(start) appears to make my sem function more robust (e.g., less
sensitive to start values when the parameters are of very different
magnitudes), but setting fscale to the log-likelihood at the start values
for the parameters seems to create problems.
Any help, advice, or additional information would be appreciated. (I plan
to take a look at the Dennis and Schnabel text cited in the help file for
nlm but have not yet done so.)
Thanks,
John
-----------------------------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario, Canada L8S 4M4
email: jfox at mcmaster.ca
phone: 905-525-9140x23604
web: www.socsci.mcmaster.ca/jfox
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