Generalized least squares using "gnls" function

ans52g <- gnls(log(b52) ~ p0 + p1/(1 + exp(-(log(dose)-p2)/p3))^p4, 

The default argument for varPower's `form' arg is form = ~fitted(.)
I am pretty sure that is the `.' that is not found, and I guess it 
is an 
S/R difference.

I've always had trouble with this form of varPower (even in S).  I 
just 
wonder if form = ~fitted(".") might work.


On Thu, 15 Jan 2004, Ravi Varadhan wrote:

Dear Christian:

That is not the problem, but thanks for your attempted help. I 

still 

don't know what the problem is.  Has anyone encountered this 

while 

using "gnls" function in the package "nlme"?

thanks again for any help,

Ravi.



----- Original Message -----
From: Christian Mora <christian_mora at vtr.net>
Date: Wednesday, January 14, 2004 7:15 pm
Subject: RE: [R] Generalized least squares using "gnls" function

Have you tried removing tol=1.e-07 or changing the value 

considering> > that the error is Object "." not found

-----Original Message-----
From: r-help-bounces+christian_mora=vtr.net at stat.math.ethz.ch
[mailto:r-help-

bounces+christian_mora=vtr.net at stat.math.ethz.ch] On

Behalf Of Ravi Varadhan
Sent: Wednesday, January 14, 2004 6:11 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Generalized least squares using "gnls" function


Hi:

I have data from an assay in the form of two vectors, one is 
response 
and the other is a predictor. When I attempt to fit a 5 

parameter 

logistic model with "nls", I get converged parameter 

estimates. I 

also 
get the same answers with "gnls" without specifying the 

"weights" 

argument.

However, when I attempt to use the "gnls" function and try to 
estimate 
the variance function, as a power function, I get the 

following 

error 
message:

ans51g <- gnls(log(b51) ~ p0 + p1/(1 + exp(-(log(dose)-

p2)/p3))^p4, 

start=list(p0=3,p1=1,p2=4,p3=2,p4=1.5),control=gnlsControl(tol=1.e-

07),weights=varPower())
Error in eval(expr, envir, enclos) : Object "." not found

What am I doing wrong here and how can I do a GLS analysis 

with a 

variance function that is estimated from the data?

Here is my data:

b51 <- c(17447.60674, 7060.37234, 2872.53012,  796.40426,  

454.47222,  260.22340,  120.11905,    83.40196,  51.45745,    
36.87912,  26.73256,    25.18681, 17.97674)

dose <- c( 1.000000e+04, 1.000000e+03, 2.500000e+02, 

6.250000e+01, 
3.125000e+01,  1.562500e+01, 7.812500e+00, 3.906250e+00, 
1.953125e+00, 9.765625e-01, 4.882813e-01, 2.441406e-01, 

1.000000e-03)

thanks for the help,
Ravi.

project.org/posting-guide.html

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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