Hi,
Peter: thank you, I have taken a look at ?approxfun but I'm not sure it does
what I'm after.
Eduardo:
The data doesn't represent functions. Basically the X values represent the
distance across a sample and the Y values are a measure of the colour
intensity at that point across the sample (i.e. a line plot across the
sample). Each data set represents a measurement across a different section
of the sample. All data sets show alternating 'light' and 'dark' sections,
though the sample isn't perfect so the widths of each section do not
entirely match up from one data set to another.
The problem comes from the fact that some data sets contain as many as 400
measurements across the sample whereas others contain as few as 150
measurements. This means that measurements do not necessarily occur at the
same value of X on different data sets. Therefore I think I need some way to
average the lines ('of best fit') that each data set creates on the graph,
rather than averaging the data ponits themselfs as I can't see how I can
take averages/weighted averages of the data points when they occur at
different values of X (and at different intervals) across the sample. Is my
description any better this time?
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