Searching for Facebook value with differential evaluation

I have mentioned recently the Facebook's IPO preparations and its desire to sell its share at the $100 billion valuation.

A little later I have read an interesting analysis of the Facebook valuation based on the logistic growth model fitting by Peter Cauwels and Didier Sornette.

Taking this opportunity, I decided to test a brute force logistic model fitting to the actual data, using both simulated annealing and differential evolution optimization methods as implemented in R.

The results of such an approach are a little but not substantially different from the Cauwels-Sornette approach, at least in the differential evaluation case:

> # p0, k, r
> x    # differential evolution
      par1       par2       par3 
  1.000000 920.729890   1.262142 
> x2   # simulated annealing
[1]   0.1005737 505.2465850   1.9097082