Message-ID: <1025a4af0905140903pb76824cje2851a81e6d3635d@mail.gmail.com>
Date: 2009-05-14T16:03:46Z
From: Dieter Wirz
Subject: automated polynomial regression
Dear all -
We perform some measurements with a machine that needs to be
recalibrated. The best calibration we get with polynomial regression.
The data might look like follows:
> true_y <- c(1:50)*.8
> # the real values
> m_y <- c((1:21)*1.1, 21.1, 22.2, 23.3 ,c(25:50)*.9)/0.3-5.2
> # the measured data
> x <- c(1:50)
> # and the x-axes
>
> # Now I do the following:
>
> m_y_2 <- m_y^2
> m_y_3 <- m_y^3
> mylm <- lm(true_y ~ m_y + m_y_2 + m_y_3) ; mylm
Call:
lm(formula = true_y ~ m_y + m_y_2 + m_y_3)
Coefficients:
(Intercept) m_y m_y_2 m_y_3
1.646e+00 1.252e-01 2.340e-03 -9.638e-06
Now I can get the real result with
> calibration <- 1.646e+00 + 1.252e-01*m_y + 2.340e-03*m_y_2 - 9.638e-06* m_y_3
But I have to put the values "by hand" into the polynom.
Isn't there an easier, more direct way, or at least , is there a way
to access the coefficients of lm() for further calculations?
Thanks
Dieter