On Wed, 3 Sep 2008, Ranney, Steven wrote:
and I'm trying to fit a simple Von Bertalanffy growth curve with program:
VonB=nls(TL~Linf*(1-exp(-k*(age-t0))), data=box5.4,
start=list(Linf=1000, k=0.1, t0=0.1), trace=TRUE)
...
Everything works as it should right up until the confint(VonB) statement.
When I ask
for the confidence intervals, R goes through the process then stops and gives
"Error in prof$getProfile() :
step factor 0.000488281 reduced below 'minFactor' of 0.000976562".
However, when I use nls.control=(minFactor=0.000001) OR
nls.control(minFactor=0.000001),
In my experience, it never helps to reduce the control factors once this error
comes up; it is a problem that by profiling you hit a boundary where
convergence problems are serious.
Suggestions: first, try with some smaller p-value, e.g. 0.8 or 0.7 instead of
the default of 0.95; profiling will stay in safer region.
It may be possible to use algorithm "port" in combination with lower/upper, but
I am not sure if this is honoured by profile.
Dieter
I adjusted the nls() statement by adding the algorithm="port" statement.
Without changing the
confint(vonB) request or including a lower/upper statement (I'm still not sure
what they do),
I was given
2.5% 97.5%
Linf 462.8386 NA
k NA 0.6944959
t0 NA 0.7973458
It's not until I get down to confint(VonB, level=.31) that I get confidence
interval values for
all of the parameter estimates in the model. Any thoughts or ideas as to why?
For the reason Dieter Menne has already told you. When profiling you are
trying to fit models that cannot be fitted. I guess you need constraints
on your parameters (as DM suggested), or perhaps better, to transform
them.
There are few things with nls profiling in R 2.7.x that are too
conservative, so you might like to try R-devel (but I suspect you will
still get into problems at 5%).
Steven H. Ranney
Graduate Research Assistant (Ph.D)
USGS Montana Cooperative Fishery Research Unit
Montana State University
P.O. Box 173460
Bozeman, MT 59717-3460
phone: (406) 994-6643
fax: (406) 994-7479
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