# Linear Regression - more weight on specific Bins of data

7 vues (au cours des 30 derniers jours)
Hoda le 28 Nov 2011
Hi, I am sort of new to Matlab and I need to analyze some data on Matlab. What I need to do is; I have a scatter plot (x, y) and I need to do a linear regression on this data in a way that I have more weight on a specific section (or bins)of my x axis.For example, my x axis is from 0 to 45, and i want to make a linear regression of the data so that I have more weight on data between 15 to 40, and less weight on data points above 40. For this I have to BIN my data points to 5 parts, (1 bin < x<15, 2 bins when x between 15 and 40 , and 1 bin when x is higher than 40). How can I do this easily in Matlab. I used polyfit for the linear regression, but how can I modify it to do such a thing. Thanks alot.
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### Réponses (3)

Richard Willey le 28 Nov 2011
MathWorks tech support has a solution documenting various options for weighted regression.
From my perspective, robustfit provides the most flexibility.
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Daniel Shub le 28 Nov 2011
+1 nice use of the documentation

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Daniel Shub le 28 Nov 2011
I am not sure you can do it easily with polyfit. The cftool and lscov both allow differential weighting.
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Michael le 28 Nov 2011
lsqnonlin may be a good place to start, rather than giving it your model function and a starting point (eg. lsqcurvefit), you give it a function which returns a vector of the residuals of the fit. This way you have the freedom to multiply these residuals by factors based on their corresponding x coordinate- if a residual is multiplied by two, the minimisation scheme in lsqnonlin should work harder to ensure that this point is close to the final curve.
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