Thanks Dieter
That solved the issue. I had negative parameters but I customized a selfStart
function which contained the following lines for the optimization of my five
parameter function (entered in the vector 'value'):
#function to optimize
func1 <- function( value) {
A = value[1]
k = value[2]
i = value[3]
Rk = value[4]
Ri = value[5]
y1<-rep(0,length(xy$x)) # a vector to hold predictions of y to compare with
observed y
for(p in 1:length(xy$x)){
y1[p]<- A*exp((-1*exp(-k*(xy$x[p]-i)))-(exp(Rk*(xy$x[p]-Ri))))} #this is my
nonlinear equation
evl<-sum((xy$y-y1)^2) #sum of squares is function to minimize
return(evl)
}
#optimization
oppar<-optim(c(A,k,i,Rk,Ri),func1,method="L-BFGS-B",
lower=c(A*.5,0.001,0,-2,Ri*0.01),
upper=c(A*2,0.5,65,2,Ri*100),control=list(maxit=2000,parscale=c(1e4,1e-2,1e1,1e-3,1e1)))
#save optimized parameters
value<-(c(oppar$par))
I also had to increase the tolerance parameter in the control section of the nlsList call to permit convergence for all individuals. I was then able to assess the fit using a trellis plot to check that they were satisfactory.
Steve
Dr. Steve Oswald
Penn State Berks
On Wed, Mar 31, 2010 02:32 AM, Dieter Menne <
[hidden email]> wrote:
> Steve Oswald wrote:
>>
>> I'm analysing growth rates using a gompertz (logistic) curve and
>am
>> attempting
>> to fit parameters for all of my study birds using nlsList.
>>
>> I've been looking for an option in nlsList to set min and max limits for
>> parameter values during estimation, although I have failed to find any
>> under
>> 'control'.
>>
>
>If you want to constrain to positive parameters only, as in pharmacology,
>fitting the logs of the parameters might help. For more general constraints,
>check the examples in optim.
>
>Dieter
>
>
>
>
>
>Hi All
>
>
>I'm analysing growth rates using a gompertz (logistic) curve and am
>attempting
>to fit parameters for all of my study birds using nlsList.
>
>
>I've been looking for an option in nlsList to set min and max limits for
>parameter values during estimation, although I have failed to find any under
>'control'. Other users seem to have reported that using control in the port
>algorithm (as in an nls fit) failed to work and it didn't work in my
>case
>either. Is there such a control for nlsList?
>
>
>I did fashion a selfStart function with a work-around loop in it. This
>subsetted the data by ID and performed separate nls fits with parameters
>constrained by the port algorithm. My objective was to use nlsList as an
>object
>for an nlme fit, so I was thinking of pasting together the details of the
>fits
>from my slefStart function into an object of class "nlsList"
>"lmList" but
>wasn't sure if this would work or was even appropriate.
>
>
>Thanks for your help
>
>
>Steve
>
>
>Dr. Steve Oswald
>
>
>Penn State Berks
>
> [[alternative HTML version deleted]]
>
>______________________________________________
>
[hidden email] mailing list
>
https://stat.ethz.ch/mailman/listinfo/r-help>PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html>and provide commented, minimal, self-contained, reproducible code.
>
>
>
>--
>View this message in context:
>
http://n4.nabble.com/nlsList-nlme-control-of-min-and-max-parameter-bounds-tp1746242p1746347.html>Sent from the R help mailing list archive at Nabble.com.
>
>______________________________________________
>
[hidden email] mailing list
>
https://stat.ethz.ch/mailman/listinfo/r-help>PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html>and provide commented, minimal, self-contained, reproducible code.
>
>
>
[[alternative HTML version deleted]]
______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide
http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
Locked
