Hi tronter, PLEASE do read the posting guide http://www.R-project.org/posting- guide.html and provide commented, minimal, self-contained, reproducible code.
Hank On Jun 7, 2007, at 5:50 PM, tronter wrote: > > Hello > > I followed the example in page 59, chapter 11 of the 'Introduction > to R' > manual. I entered my own x,y data. I used the least squares. My > function has > 5 parameters: p[1], p[2], p[3], p[4], p[5]. I plotted the x-y data. > Then I > used lines(spline(xfit,yfit)) to overlay best curves on the data while > changing the parameters. My question is how do I calculate the > residual sum > of squares. In the example they have the following: > > df <- data.frame( x=x, y=y) > > fit <- nls(y ~SSmicmen(s, Vm, K), df) > > fit > > > In the second line how would I input my function? Would it be: > > fit <- nls(y ~ myfunction(p[1], p[2], p[3], p[4], p[5]), df) where > myfunction is the actual function? My function doesnt have a name, > so should > I just enter it? > > Thanks > > -- > View this message in context: http://www.nabble.com/Nonlinear- > Regression-tf3886617.html#a11016968 > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@stat.math.ethz.ch 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. ______________________________________________ R-help@stat.math.ethz.ch 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.