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Tags

#chracterization #computation #social-choice #voting-rules

Question

Borda Rule as Maximum Likelihood Estimator: If each voter independently ranks the true winner out of m alternatives at position k with probability [...] , then the maximum likelihood estimator is the Borda rule.

Answer

\(\frac{2^{m−k}} {2^{m −1}}\)

Tags

#chracterization #computation #social-choice #voting-rules

Question

Borda Rule as Maximum Likelihood Estimator: If each voter independently ranks the true winner out of m alternatives at position k with probability [...] , then the maximum likelihood estimator is the Borda rule.

Answer

?

Tags

#chracterization #computation #social-choice #voting-rules

Question

Borda Rule as Maximum Likelihood Estimator: If each voter independently ranks the true winner out of m alternatives at position k with probability [...] , then the maximum likelihood estimator is the Borda rule.

Answer

\(\frac{2^{m−k}} {2^{m −1}}\)

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#### Parent (intermediate) annotation

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Borda Rule as Maximum Likelihood Estimator: If each voter independently ranks the true winner out of m alternatives at position k with probability \(\frac{2 m−k} {2 m −1}\) , then the maximum likelihood estimator is the Borda rule.

#### Original toplevel document (pdf)

owner: rappatoni - (no access) - comsoc-characterisation-2017 (1).pdf, p13

Borda Rule as Maximum Likelihood Estimator: If each voter independently ranks the true winner out of m alternatives at position k with probability \(\frac{2 m−k} {2 m −1}\) , then the maximum likelihood estimator is the Borda rule.

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
---|---|---|---|---|---|---|---|

repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

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