Have to thank Graham for putting up this topic of QBO predictability.

I was going through some old Eureqa machine leaning experiments on QBO and once again realized the significance of what it found.


Started with raw QBO data
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![rawQBO](http://imageshack.com/a/img540/8111/JVyVPG.gif)

Next targeted a solution with sinusoidal factors
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maximizing correlation coefficient

![params](http://imageshack.com/a/img911/1995/eW8IQg.gif)

Then let Eureqa crank away for 20 hours
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![prog](http://imageshack.com/a/img905/707/l573Zu.gif)

Picked a high complexity solution
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(high complexity doesn't matter as the other solutions have similar components)


![soln](http://imageshack.com/a/img540/9429/S7WLD8.gif)


The two strongest factors that Eureqa found
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which were sinusoids with an obviously folded or aliased frequency

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strength aliased freq period days actual % error
78 2.66341033 2.359075219 27.20894362 27.212=draconic 0.011233004
35 2.29753386 2.734751989 29.53743558 29.531=synodic -0.021787874
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The two factors have periods when unaliased that match the draconic and synodic lunar month, with errors 0.01% and 0.02% respecively
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What are the chances of that?