Generalized least squares using "gnls" function
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.
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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) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595