[R] Non-Linear Quantile Regression

Philippe Grosjean phgrosjean at sciviews.org
Tue Jan 1 15:25:56 CET 2008


Hello,

You use nlrq() pretty much the same as nls(). Look at ?nls and you will 
find there many examples on how to use it. The easiest way is to use 
with a "self-start model". Do apropos("^ss") to get the list of 
self-starting models defined, and look at their respective help pages to 
see if one would fit your needs.
Best,

Philippe Grosjean

Humberto Marotta wrote:
> Please,
> 
> I have a problem with nonlinear quantile regression.
> 
> My data shows a large variability and the quantile regression seemed perfect
> to relate two given variables. I got to run the linear quantile regression
> analysis and to build the graph in the R  (with quantreg package). However, the
> up part of my data dispersion seems a positive exponential curve, while the
> down part seems a negative exponential curve. The median part seems linear
> (maybe non-significant). I think that I needs  to run a non-linear quantile
> regression for this dataset (including a tau = 0.1, 0.25, 0.5, 0.75 and 0.90
> ).
> 
> The problem is: I read very much many manuals about Quantile regression and
> the operational use of R, but I did not get to put parametrs in R to run
> this non-linear analysis.
> 
> Might the function in R be the following?
> nlrq(formula, data=parent.frame(), start, tau=0.5, control,
> trace=FALSE,method="L-BFGS-B")
> 
> What's the formula I could put here for my data?? How I put my file in this
> function? Might it  be as [scan(file=read.dat" ]?? But where?
> 
> At last, one confirmation: Can I run log X log analysis in nlrq??
> 
> Please, I need very much any response, as I don't know what make in this
> moment...
> 
> Thank you very much,
> Humberto Marotta
> 
> phD Student from Federal University of Rio de Janeiro
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help at 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.
>




More information about the R-help mailing list