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Forecasting 🇫🇷 elections with Bayesian statistics 🥳

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This should be kept out of the model class, which should only check the validity of the data it is fed.

Presidential Elections

The Ornstein-Uhlenbeck kernel defines a stationary gaussian process that describes a mean-reverting stochastic process. It seems more adapted to our modeling problem than a gaussian kernel that doesn't have an...

Presidential Elections

Voter uncertainty can change the conclusions dramatically, especially early in the campaign where close to 50% of poll respondants say they could still change their mind. It is thus important...

Presidential Elections

Led by @rlouf by front-end dev help welcome!

Presidential Elections

Try and see whether switchers can be consistently included into the two-part dynamic model -- both statistical feasability and availability of data in polls

Presidential Elections

Try and see whether non-voters can be consistently included into the two-part dynamic model -- both statistical feasability and availability of data in polls

Presidential Elections

Which would allow us to study how intentions flow between candidates from one poll to the next. This is especially important in an election with 2 rounds.

Presidential Elections