Suppose I have a set of 100 $n \times 2$ matrices that all have the following format:
Bid Profit [5.00 7.10] [3.14 6.04] [2.9 10.08]
Where the numbers are sample values. Now I want to cluster these matrices together using
R or some statistical software. How can I do this? I've looked into
hclust and time series clustering in
R but I don't think this is what I want.
In the attached picture, I have three sample matrices plotted. For simplicity's sake I have plotted them all with the same x-values but this may not necessarily be the case. I want a way of saying "at points 3,8,9 (the three highest points on the black curve), this black curve is similar to the blue curve but not the red curve". Ordering of the rows of the matrix should not matter - I can just sort by the first column to ensure that the x-values (Bid) are ordered least to greatest.
These graphs are included as if the first column in all three matrices was the same i.e., all three matrices had the form
xval yval [a x1] [b x2] [c x3] [d x4] ...
and then the matrices are plotted with the first column on the x-axis and the second column on the y-axis.