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Forecasting 🇫🇷 elections with Bayesian statistics 🥳
This should be kept out of the model class, which should only check the validity of the data it is fed.
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...
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...
Led by @rlouf by front-end dev help welcome!
Try and see whether switchers can be consistently included into the two-part dynamic model -- both statistical feasability and availability of data in polls
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
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.