Saturday, June 20, 2009

H1N1 ... again

I'm always amused by the "mathematical" fitting of curves to the worldwide cases of H1N1 virus.

I started with the standard Logistic fit.
How well the curve fits the data is measured by the Root-Mean-Square (RMS) error.
That currently gives this:

Note the predicted Eventual Value.

I migrated to a sexier curve, with more parameters and a Weighted error (where the recent errors are weighted more heavily than the ancient ones)... and I got this:

Note the predicted Eventual Value.

Of course, one could assume (almost) any curve with sufficiently many parameters and get a reasonable fit.
Indeed, even something simple like: y = A xb gives a respectable fit:

However, it's that Eventual Value that should be reasonable.

von Newmann said:
"With four parameters I can fit an elephant and with five I can make him wiggle his trunk."

 

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