Re: [R] lm coefficients

[Spencer Graves]

     The function "poly" produces orthogonal polynomials, and those 
depend on the exact combinations of levels of X in "d".  Consider the 
following: 

> round(poly(1:3, 2), 2)
        1     2
[1,] -0.71  0.41
[2,]  0.00 -0.82
[3,]  0.71  0.41
> round(poly(1:4, 2), 2)
        1    2
[1,] -0.67  0.5
[2,] -0.22 -0.5
[3,]  0.22 -0.5
[4,]  0.67  0.5
     Does this answer your question? 
     spencer graves

Timur Elzhov wrote:

Dear R experts,

Excuse me if my question will be stupid...
I'd like to fit data with x^2 polynomial:
d <- read.table(file = "Oleg.dat", head = TRUE)
d
 X         T
 3720.00   4.113
 3715.00   4.123
 3710.00   4.132
 ...
out <- lm(T ~ poly(X, 4), data = d)
out
 Call:
 lm(formula = T ~ poly(X, 2), data = d)
 
 Coefficients:
 (Intercept)  poly(X, 2)1  poly(X, 2)2  
       9.803     -108.075       51.007  

So, d$T best fitted with function
 9.803 -108.075 * X + 51.007 * X^2,
yes?
T1 <- 9.803 -108.075 * d$X + 51.007 * d$X^2
T1
 705453240
 703557595
 701664500
 699773956
 ...
So, T1 obviosly gets non-sensible values.. :( Why?
Thanks a lot!
--
WBR,
Timur.
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