# devrand/bayesian_vote_transfer

How many voters for each candidate in first round of election, voted for candidate X in second round? Ukrainian presidential election-2019 example
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# bayes_vote_transfer

Use bayesian linear regression to find how many voters for each candidate in first round of election, voted for candidate X in second round? Based on real data from each poll station on Ukrainian presidential election-2019.

What are the assumptions of a model:

• all standart assumptions for bayesian linear regression
• there are different levels of support for each candidates in second round from different group of voters in first round (each group - voters who voted for some candidate) (uniforms as priors)
• turnout modelled for each such group as different parameters, too (student as priors)
• final share of voters for candidate Z from first tour, who voted for candidate X in second, is a multiple of level of support for candidate X and turnout for this group of voters: total_x * turnout
• finally, on each poll station, sum of all total_x[i] * turnout[i] * votes_from_first_round[i] == number of votes for X in second round, where i - index of each different group of voters, and votes_from_first_round[i] - rezult for group i on this station.

## Result for Poroshenko

Also, see here in Ukrainian:

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