Re: [R] Non-linear regression/Quantile regression

2009-06-09 Thread Gabor Grothendieck
; 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:

Re: [R] Non-linear regression/Quantile regression

2009-06-09 Thread Greg Snow
n...@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 differe

Re: [R] Non-linear regression/Quantile regression

2009-06-09 Thread Ravi Varadhan
half Of despaired Sent: Tuesday, June 09, 2009 11:59 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?

Re: [R] Non-linear regression/Quantile regression

2009-06-09 Thread despaired
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

Re: [R] Non-linear regression/Quantile regression

2009-06-09 Thread Gabor Grothendieck
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 wrote: > > Hi, > > I'm relatively new to R and