The example shows the results from slow autopilot for a particular data set.
Because it had the "slow" setting of autopilot, it attempts 6D down through 1D
solutions.
Several points to notice about these graphs:
 Curves for higher dimensionalities have lower final stress than curves for lower
dimensionality.
That is because it is easier to fit the data with more dimensions in the solution.
 Curves for the randomized runs have higher final stress values than the curves for the
real runs.
This is because the real data have a correlation structure among the variables that allows
a lower stress solution.
 Curves for the real runs are more variable for a given dimensionality than the
randomized runs.
 A few real curves have rather high instability, as shown by their jagged shape.
