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,
St?phane
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