[R] Puzzling coefficients for linear fitting to polynom

[Dimitris Rizopoulos]

poly() computes by default orthogonal polynomials; check the online 
help file for poly() for more info. Probably you want to use the 'raw' 
argument in this example, i.e.,

x <- 1:3
y <- c(1, 4, 9)
lm(y ~ poly(x, 2, raw = TRUE))


I hope this helps.

Best,
Dimitris

----
Dimitris Rizopoulos
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
     http://www.student.kuleuven.be/~m0390867/dimitris.htm


----- Original Message ----- 
From: "Firas Swidan, PhD" <frsswdn at gmail.com>
To: <r-help at r-project.org>
Sent: Friday, March 07, 2008 9:16 AM
Subject: [R] Puzzling coefficients for linear fitting to polynom


> Hi,
>
> I can not comprehend the linear fitting results of polynoms. For
> example, given the following data (representing y = x^2):
>
>> x <- 1:3
>> y <- c(1, 4, 9)
>
> performing a linear fit
>
>> f <- lm(y ~ poly(x, 2))
>
> gives weird coefficients:
>
>> coefficients(f)
> (Intercept) poly(x, 2)1 poly(x, 2)2
>  4.6666667   5.6568542   0.8164966
>
> However the fitted() result makes sense:
>
>> fitted(f)
> 1 2 3
> 1 4 9
>
> This is very confusing. How should one understand the result of
> coefficients()?
>
> Thanks for any tips,
> Firas.
>
> -- 
> Firas Swidan, PhD
> Founder and CEO
> Olymons: Blessing Machines with Vision (TM)
> http://www.olymons.com
> P.O.Box 8125
> Nazareth 16480
> Israel
> Cell: +.972.(0)54.733.1788
>
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> 


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