Dear list,
I want to apply the same nls function to different subsets of a larger dataset. These subsets are defined as unique combinations of two (categorical) variables, each one with two levels, so I should obtain 4 sets of parameters after fitting. I have managed to do it in a loop, creating different datasets for each one of the sub-groups, and then applying the function to each one independently and finally just merging all parameters in a single dataset, but this seems pretty inefficient. I tried to use by and with, but they don't produce the expected result. Rather, I get 4 sets of exactly the same parameters (?), so I know that with/by are not actually doing anything, and the function is applied tothe dataset as a whole. Here is the call I tried to use: test <- with(Data, by(Data, list(Type, Phase), function(x) nls(Response ~ k*exp(-((Duration-mu)^2)/(2*sigma^2)), start=c(mu=0,sigma=150,k=0.9), upper=c(Inf, Inf, 1), algorithm="port", trace=T, control=CSJ_FitControl))) Also, I would like to plot the fitted distributions for each sub-group in the same plot to be able to directly compare them. I figured that, since I have the base nls function and the resulting parameters for each subset (stored in a data frame), I should be able to enter these on a ggplot call to get the 4 regressions lines plotted along with the data, but I can't get that to work either. Or is it necessary to plot this at the fitting stage (i.e. with the original data)? Thanks for any suggestion ______________________________________________ [hidden email] 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. |
Given that nls() often gives failures of the "singular gradient" type, you may want to give package nlsr a try with the
nlxb() function. It should be able to use analytic gradients on this expression, has bounds, and uses a Marquardt stabilized solver. It can still fail, but is more robust than nls(). I suspect that explicit looping is a safer way to proceed than trying to use by() within with(). Looping is not the slow part of this set of computations. JN On 2017-03-11 10:37 AM, DANIEL PRECIADO wrote: > Dear list, > > I want to apply the same nls function to different subsets of a larger > dataset. These subsets are defined as unique combinations of two > (categorical) variables, each one with two levels, so I should obtain 4 > sets of parameters after fitting. > > I have managed to do it in a loop, creating different datasets for each > one of the sub-groups, and then applying the function to each one > independently and finally just merging all parameters in a single > dataset, but this seems pretty inefficient. > > I tried to use by and with, but they don't produce the expected result. > Rather, I get 4 sets of exactly the same parameters (?), so I know that > with/by are not actually doing anything, and the function is applied tothe dataset as a whole. > > Here is the call I tried to use: > > test <- with(Data, by(Data, list(Type, Phase), function(x) nls(Response > ~ k*exp(-((Duration-mu)^2)/(2*sigma^2)), start=c(mu=0,sigma=150,k=0.9), > upper=c(Inf, Inf, 1), algorithm="port", trace=T, > control=CSJ_FitControl))) > > Also, I would like to plot the fitted distributions for each sub-group > in the same plot to be able to directly compare them. I figured that, > since I have the base nls function and the resulting parameters for > each subset (stored in a data frame), I should be able to enter these > on a ggplot call to get the 4 regressions lines plotted along with the > data, but I can't get that to work either. Or is it necessary to plot > this at the fitting stage (i.e. with the original data)? > > Thanks for any suggestion > ______________________________________________ > [hidden email] 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. > ______________________________________________ [hidden email] 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. |
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