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Gustav Fredell
Minimizing distance (not square of distance) of linear fit to data points
Gustav Fredell
Posted
10 years ago
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Hi all,
I have a set of data {x1, y1}, {x2, y2}...
Is it possible to fit a regression line to this data that minimizes the total distance from the line to my data points? This would be better than Least-Squares in this instance.
Thank you
POSTED BY:
Gustav Fredell
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Daniel Lichtblau
Daniel Lichtblau, Wolfram Research
Posted
10 years ago
From the wording it appears that you are looking for a "total least squares" result. That can be done using the singular values decomposition.
POSTED BY:
Daniel Lichtblau
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Sander Huisman
Sander Huisman, University of Twente
Posted
10 years ago
Gustace, I don't think it will take into account the 'horizontal' difference, only the vertical distance. Calculating the closest distance to a line is a little tricky, but can be done of course.
POSTED BY:
Sander Huisman
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Gustav Fredell
Gustav Fredell
Posted
10 years ago
I think I solved the problem myself by using:
FindFit[{dataset}, a + b x, {a, b}, x, NormFunction -> (Norm[#, Infinity] &)]
Thanks for looking.
POSTED BY:
Gustav Fredell
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