Battle for White House 2016

Also for the 2016 USA election, I will periodically post election polls for the battle for White House using Bayesian methods based on near-ignorance prior probabilities that automatically allows to perform swing scenarios (e.g.,
a percentage of voters decide to change their vote). This is the first result with using June polls. In future posts, I will add a more   deeper analysis of swing scenarios. At the moment,  the result is that Hilary Clinton will win the election with very high probability.

The statistical analysis has been performed
by using the most recent polling data from here. The minimum sample size is around 500 people. The analysis employs
an imprecise probability robust Bayesian approach in which robustness is
evaluated with respect to the following swing scenarios:

    1. Best for Clinton: in each state the preference of c=2 people among the n polled is changed from Trump to Clinton.
    2. Best for Trump: in each state the preference of c=2 people among the n polled is changed from Clinton to Trump.

In
practice, we are assuming that two voters in each State lied during
the poll (or changed their mind) and we test how this affects the
prediction of the election result.
These two cases are naturally obtained by applying a Bayesian approach
in which
prior ignorance is modelled through a set of near-ignorance prior probabilities.
Under this view, changing the preference of the 2 voters is equivalent
to test the robustnees of the inferences to the choice of the prior
model.

The probability of winning of the two candidates is shown in the
following bar-plot, where the blue-bar refers to the “Best for Clinton”
case
and the red-bar to the “Best for Trump” case. In the “worst for Clinton”
case, the probability of winning of Clinton is 95% and, thus, the
probability in favour of Trump is just 5% (the blue bars).


The probability distribution of the electoral votes in the two extreme cases is shown in the following histogram.
(light red histogram is “Best for Romney”,  light blue histogram is “Best for Clinton”) together with
the 50-50 line (equal to 269 electoral votes).


From the histogram, it can be noticed that
at the moment there is not much uncertainty. Clinton is going to win the election with very high probability.

This is the electoral map for the 95% case (blue Democrat, red Republican).

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