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  0.1005737 505.2465850 1.9097082