Dear Fred

On 26/11/14 12:15, Fred Labrosse wrote:

I'm obviously missing something somewhere.  I'm playing with robust linear
fit and experimenting with a number of ways of doing it.  So far I have
tried GSL and I get the attached result (each line is a point, giving x, y,
ordinary least square fit and a robust fit (bisquare)).  I plotted that in
veusz to verify this was making sense, and it does.

Then I tried the fit in veusz, specifically a linear fit (function a + bx).
What I get does not make sense (sloping down, going from the first to the
last (outlier) points).  I restricted the range to ignore the outliers and
the fit is much better but still wrong.

What is going on?  What am I missing?

Did you provide an error bar or uncertainty on your y data? Veusz does a chi-squared minimisation and by default assumes 10% of the data value if not given an uncertainty. This probably is not a good choice for non-logarithmic data. You could try adding a symmetric error to the data value and refitting.

I just tried using 'y,0.1' as the y Data setting (this adds an error bar of 0.1 to your y data set) - this seems to give a fit similar to your least square result.

Best wishes

jeremy


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