Hello everybody
I want to use rls() on a multi-dimensional function, where parts of it are
modeled using a spline.
I tried to condense my problem into the following code example,
which tries to fit the y-values of a spline interpolation:
---------------------------------------------------------------------------
rm(list=ls(all=TRUE))
x<-c(1,2,3,4,5,6,7,8,9)
y<-x^2
f<-function(x,c1,c3,c6,c9){
ys<-spline(c(1,3,6,9),y=c(c1,c3,c6,c9),xout=x)$y
print(ys)
print(c1)
return(ys)
}
print('Function evaluation')
f(x,1,1,1,1)
f(x,1,1,1,2)
print('Fit')
fit<-nls(y~f(x,c1,c3,c6,c9),start=list(c1=1,c3=1,c6=1,c9=1),
control=nls.control(maxiter=5))
-------------------------------------------------------------------
When I run the program, nls() does not change the parameters c1,c3,c6,c9,
and the iteration does no converge (here stopped after maxiter).
Moreover, ys always contains y=x^2 for some odd reason.
Using splinefun instead does no change the result.
Is there something with scope rule I do not understand?
Any ideas?
Kind regards
Florian Hengstberger
DI Dr. FLORIAN HENGSTBERGER
Energy Department
Sustainable Thermal Energy Systems
AIT Austrian Institute of Technology GmbH
Giefinggasse 2 | 1210 Vienna | Austria
T +43(0) 50550-6609 | M +43(0) 664 6207849 | F +43(0) 50550-6679
florian.hengstber...@ait.ac.at | http://www.ait.ac.at
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