Hello, I have done some research about breakpoints (I am not a statistician) and I found out about the breakpoint, strucchange and segmented packages in R allowing to find breakpoints assuming linear model.
However, I would like to fit a periodic time series with a non linear (periodic) model, and I was wondering how I could find breakpoints for this model in R. Is it even possible ? My model is an asymmetric gaussian fitting (cf http://www.nateko.lu.se/personal/Lars.Eklundh/Institutionssida/IEEE_TGRS_timesat.pdf) with a linear-time-dependant amplitude (I am fitting this model over the whole time series). *My ideas * 1) I guess I am more interested in the breakpoints of the "amplitude" of my periodic function, so that I could assume a model of the form: Y ~ (a + b*t)*f(t), with |f(t)| <= 1, where f is a periodic function to be fitted to a non linear model, but where no breakpoints should occur. So basically, the breakpoints would only happen in the (a,b) pair of coefficients, which would be a linear regression. However, as f is unknown, this makes things harder and I don't have a lot of extremas (min/max) to detect breakpoints robustly... 2) To detect breakpoint with an harmonic model and then to apply my non linear regression on each segment. These two ideas could potentially work, however these are workarounds. Thank you for your advices ! -- View this message in context: http://r.789695.n4.nabble.com/Breakpoints-and-non-linear-regression-tp4649072.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org 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.
