# [R] nls.control()

From: Ranney, Steven <steven.ranney_at_montana.edu>
Date: Tue, 02 Sep 2008 15:56:05 -0600

All -

I have data:

```TL	age
388	4
418	4
438	4
428	5
539	10
432	4
444	7
421	4
438	4
419	4
463	6
423	4
```

...
[truncated]

#Creates a Von Bertalanffy growth model
VonB=nls(TL~Linf*(1-exp(-k*(age-t0))), data=box5.4,

start=list(Linf=1000, k=0.1, t0=0.1), trace=TRUE)
#Scatterplot of the data

plot(TL~age, data=box5.4, pch=19, xlab="Age (yr)", ylab="Total length (mm)")
#Incorporates the model VonB onto the called scatterplot
mod1a=seq(2, 11, by=0.001)
lines(mod1a, predict(VonB, list(age = mod1a)), col="blue", lwd=2)

#summarizes the model VonB with the model formula, parameter estimates, std. errors,
#and a correlation matrix

summary(VonB, corr=T)
#Provides 95% confidence intervals for the parameter estimates
confint(VonB)

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), I get the same error. I'm at a loss. I'm not sure what else I can do to have R reduce the step size if it's not nls.control().

Thanks,

SR

Steven H. Ranney

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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