[R] poly.transform in R

[Dupas Stéphane]

Dear all,

I am trying to transform polynomial coefficients from orthogonal form to 
the standard power basis. There's poly.transform in S-plus. Does anybody 
know how to do that in R ? I've found question about that in the 
archives of R-help but no real answer.

Example : I'm doing polynomial regression of percentage of one insect in 
a community on altitude, precipitations, evapotranspiration, max and min 
temperatures using glm. I would like to get the standard coordinates of 
my polynom in order to draw maps, get the maximum values, etc...

Call:
glm(formula = Ymat ~ poly(Alt, 2) + poly(Pmm, 2) + poly(E0, 2) +
    poly(Min, 2) + poly(Max, 2), family = binomial, data = tableau)

Deviance Residuals:
     Min        1Q    Median        3Q       Max
-15.5168   -0.1223    0.1085    3.5095   14.0412

Coefficients:
               Estimate Std. Error z value Pr(>|z|)
(Intercept)    -3.82301    0.16770 -22.797  < 2e-16 ***
poly(Alt, 2)1  84.65329    2.70398  31.307  < 2e-16 ***
poly(Alt, 2)2 -36.47269    1.54303 -23.637  < 2e-16 ***
poly(Pmm, 2)1   7.09874    0.37281  19.041  < 2e-16 ***
poly(Pmm, 2)2   0.01416    0.38110   0.037   0.9704
poly(E0, 2)1   -1.55123    0.69573  -2.230   0.0258 *
poly(E0, 2)2    1.51602    0.60352   2.512   0.0120 *
poly(Min, 2)1  17.57537    3.29233   5.338 9.38e-08 ***
poly(Min, 2)2  23.08318    2.10827  10.949  < 2e-16 ***
poly(Max, 2)1   9.07420    1.34201   6.762 1.36e-11 ***
poly(Max, 2)2  -0.72398    0.97286  -0.744   0.4568


---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 23381.9  on 64  degrees of freedom
Residual deviance:  1508.2  on 54  degrees of freedom
AIC: 1713.4

Number of Fisher Scoring iterations: 7



(I'd like to analyze the results of my multiple polynomial regression 
with R : maximums, zeros, etc... ?)

Thanks for your help,

Stéphane


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