Fitting a vector to another
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I have two vectors x1 and x2 (2 data sets) of two sensors measuring the same value (redundancy measurement). Correlation is almost 0.99). I want to adjust one vector (x1) to another (x2) (using other as a reference). I am currently doing 1x/x2 (simple normalization). Any other options? Thanks
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Image Analyst
on 8 Jul 2014
Give a small example. Let's say x1=[1,2,3] and x2 = [1.110, 1.999, and 3.042]. What do you want as output?
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John D'Errico
on 8 Jul 2014
Edited: John D'Errico
on 8 Jul 2014
You are the one, the only one, who can make a decision like this.
You have posed an implicit model:
x1 = k*x2 + e
where k is an unknown parameter to be found in your calibration scheme, and e is a vector of errors.
So the question is what model do YOU think makes sense? Then we can see how to estimate it. For example, might there be a constant offset on one axis or the other?
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