On Dec 13, 2010, at 9:21 PM, Bastiaan Bergman wrote:
That doesn't work, one would get two different answers depending on
the
order of execution.
The physics is: Overlay error on a Silicon wafer. One wafer has many
flash
fields, each flash field has multiple locations where the overlay
error is
measured (as: dX,dY offset). If one contemplates that the error is
caused by
a rotation of the flash field then we can say (dX,dY)=(-Y,X)*RotAngle.
Some sort of linearized approximation of a rotation matrix?
If in
addition we have a scaling error: (dX,dY)=(X*XScale,Y*YScale) than
the total
model is:
dX~X*XScale-Y*RotAngle
dY~Y*YScale+X*RotAngle
Now I want to find the values for XScale, YScale and RotAngle
... that does _what_? Minimize the sum of squares of dY and dX?
Length(dX)==length(dY)==length(X)==length(Y)==number of measured
sites on a
wafer
So dY and dX are measured and X and Y are measured how many times?
And are we doing this for several different wafers so that we need to
have nested models that incorporate an error term for each wafer? (And
if that is the case this may need to be transferred to the mixed-
models mailing list or at the very least answered by someone with a
better ax swing for such complexities that I can wield.)
--
David
Hope this clarifies...
-----Original Message-----
From: David Winsemius [mailto:dwinsem...@comcast.net]
Sent: Monday, December 13, 2010 6:06 PM
To: Bastiaan Bergman
Cc: r-help@r-project.org
Subject: Re: [R] multivariate multi regression
On Dec 13, 2010, at 8:46 PM, Bastiaan Bergman wrote:
Hello,
I want to model my data with the following model:
Y1=X1*coef1+X2*coef2
Y2=X1*coef2+X2*coef3
Note: coef2 appears in both lines
Xi, Yi is input versus output data respectively
How can I do this in R?
I got this far:
lm(Y1~X1+X2,mydata)
now how do I add the second line of the model including the cross
dependency?
The usual way would be to extract coef2 from the object returned from
the first invocation of lm(...) and use it to calculate an offset
term in a second model. It would not have any variance calculated
since you are forcing it to be what was returned in the first model.
Now, what is it that you are really trying to do with this procedure?
--
David Winsemius, MD
West Hartford, CT
______________________________________________
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.
