Dieter Wirz wrote:
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.
Hi Dieter,
The lm() function will create an object with members that can easily be
accessed. Just save the result of your regression in a variable and
output the needed quantity. For example,
mylm <- lm(true_y ~ m_y + m_y_2 + m_y_3) ;
## Now, what I believe you're looking for ;
mylm$coefficients ;
Cheers,
--
*Luc Villandré*
/Biostatistician
McGill University Health Center -
Montreal Children's Hospital Research Institute/
______________________________________________
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.
