Hello all!
In natural sciences you often encounter absolute maximum errors resulting
from inaccurate measuring instruments. Maximum errors also occur when you
estimate how precicely you can read a scale of a measuring instrument. If
you have a dataset with different absolute errors in the x-values and
different absolute errors in the y-values, is it possible to fit a staight
line to this dataset, taking into account these different errors? Can you
estimate the (maximum) error of slope and constant term of the regression
line? I know there's an iterative method [D. York, Can. J. Phys. 44,
pp.1079, 1966 or http://www.uio.no/~olews/stat/lsq.html] concerning a
similar problem, but this method refers to different standard deviations of
x and y and thus supplies standard deviations of slope and constant term. I
don't see any opportunity of using this method as, in this case, I have to
consider absolute maximum errors. Does anybody know a method to handle this
problem? Any comments, references etc. are welcome.
Many thanks in advance!
Stefan
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