poly by default uses orthogonal polynomials which work better mathematically but are harder to interpret. See ?poly -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare greg.s...@imail.org 801.408.8111
> -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r- > project.org] On Behalf Of despaired > Sent: Tuesday, June 09, 2009 9:59 AM > To: r-help@r-project.org > Subject: Re: [R] Non-linear regression/Quantile regression > > > Hi, > > thanks, it works :-) > But where is the difference between demand ~ Time + I(Time^2) and > demand ~ > poly(Time, 2) ? > Or: How do I have to interpret the results? (I get different results > for the > two methods) > > Thank you again! > > > Gabor Grothendieck wrote: > > > > Those are linear in the coefficients so try these: > > > > library(quantreg) > > > > rq1 <- rq(demand ~ Time + I(Time^2), data = BOD, tau= 1:3/4); rq1 > > > > # or > > rq2 <- rq(demand ~ poly(Time, 2), data = BOD, tau = 1:3/4); rq2 > > > > > > On Tue, Jun 9, 2009 at 10:55 AM, despaired<meyfa...@uni-potsdam.de> > wrote: > >> > >> Hi, > >> > >> I'm relatively new to R and need to do a quantile regression. Linear > >> quantile regression works, but for my data I need some quadratic > >> function. > >> So I guess, I have to use a nonlinear quantile regression. I tried > the > >> example on the help page for nlrq with my data and it worked. But > the > >> example there was with a SSlogis model. Trying to write > >> > >> dat.nlrq <- nlrq(BM ~ I(Regen100^2), data=dat, tau=0.25, trace=TRUE) > >> > >> or > >> > >> dat.nlrq <- nlrq(BM ~ poly(Regen100^2), data=dat, tau=0.25, > trace=TRUE) > >> > >> (I don't know the difference) both gave me the following error > message: > >> > >> error in getInitial.default(func, data, mCall = > as.list(match.call(func, > >> : > >> no 'getInitial' method found for "function" objects > >> > >> Looking in getInitial, it must have to do something with the > starting > >> parameters or selfStart model. But I have no idea, what this is and > how I > >> handle this problem. Can anyone please help? > >> > >> Thanks a lot in advance! > >> -- > >> View this message in context: > >> http://www.nabble.com/Non-linear-regression-Quantile-regression- > tp23944530p23944530.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. > >> > > > > ______________________________________________ > > 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. > > > > > > -- > View this message in context: http://www.nabble.com/Non-linear- > regression-Quantile-regression-tp23944530p23945900.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. ______________________________________________ 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.