Finding starting values is a bit of a dark art. That said, there are steps you can take, but it may take time.
First, I would scale Year so that it's not in the thousands! Experiment with subtracting 1980 or so. For specific advice, see inline. On Thu, Feb 26, 2015 at 3:03 AM, Corey Callaghan <ccallaghan2...@fau.edu> wrote: > The curves' functions that I want to test are in the code here (hopefully > correctly): > > Inverse Quadratic Curve: > fitmodel <- nls(Area ~ (-a*Year)*(Year + b), data = df, start=list(a=??, > b=??, c=??)) > I would plot the data and a smooth spline, differentiate the curve function, identify some parameter values somewhere stable, and estimate some values by eye, or even predict them from the first derivative of the spline - spline.smooth will do this. Sigmodial Curve: > fitmodel <- nls(Area~a/(1+exp(-(b+c*Year))), data=df, start=list(a=???, > b=???, c=??)) > I'd use the highest value as a, fit spline as above then invert area at two times to get b and c. Double sigmoidal Curve: > fitmodel <- nls(Area~a+2b(1/(1+exp(-abs(-c*Year+d)))-1/2)*sign(-c*Year+d), > data=df, start=list(a=???, b=???, c=???) > I'd use min(Area) as a, figure out b from the maximum (I guess 2b+a is the asymptote), and experiment with two values for year to retrieve c and d .... uniroot might help? Cheers Andrew -- Andrew Robinson Deputy Director, CEBRA, School of Biosciences Reader & Associate Professor in Applied Statistics Tel: (+61) 0403 138 955 School of Mathematics and Statistics Fax: +61-3-8344 4599 University of Melbourne, VIC 3010 Australia Email: a.robin...@ms.unimelb.edu.au Website: http://www.ms.unimelb.edu.au/~andrewpr MSME: http://www.crcpress.com/product/isbn/9781439858028 FAwR: http://www.ms.unimelb.edu.au/~andrewpr/FAwR/ SPuR: http://www.ms.unimelb.edu.au/spuRs/ [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
