Puzzling coefficients for linear fitting to polynom

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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