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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
