[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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