Thursday, February 21, 2013
Best fit step
Consider "fitting" a step shape (in red) to data (in blue) by simply matching step height to data height and choosing the first place the (lower) level encounters the data.
Once you have aligned the abstraction (in red) over the data (in blue) you can do a least squares fit. [This is the only evidence I have of the value of least squares best model.]
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Solving this problem at work, whose specific content cannot be described for legal reasons, forced me to formalize the approach as a mathematical equation (which is given in the next post). Taken together, the two posts, represent a turning point (or rather a high point) in my intellectual life.
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