US2016 election forecast

I have run again the Bayesian algorithm that uses a prior near-ignorance model to compute US2016 election forecast.
This is the current situation for Clinton (worst-case in red and best-case in blue).
The probability range of winning the election (by getting the majority of the electoral votes) is [0.68,0.91]. The posterior distributions obtained using the
prior near-ignorance model are shown in figure:

The state by state situation is the following

The most uncertain states at the moment are

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