# bayes: Probabilities in a brazilian electoral pool In filipezabala/desempateTecnico: desempateTecnico

## Description

Calculates posterior probabilities via Monte Carlo.

## Usage

 `1` ```bayes(p = vector(), n, p.nv = 0, p.und = 0, M = 10^4) ```

## Arguments

 `p` A vector containing the proportions of votes. `n` Sample size. `p.nv` A number containing the proportion of non valid votes to be excluded. Default: `0`. `p.und` A number containing the proportion of undecided votes to be proportionally distributed considering p and p.nv. Default: `0`. `M` Number of replications. Default: `10^4`.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```bayes(c(.4,.3,.3), 1000) bayes(c(.3,.25,.2,.1,.05), 100) bayes(rep(1/5,5), 500) # Contando com não válidos (p.nv) e indecisos (p.und) # https://www.cnnbrasil.com.br/politica/2021/03/10/pesquisa-exclusiva-cnn-mostra-bolsonaro-em-1-dez-pontos-a-frente-de-lula bayes(p=c(.31,.21,.10,.09,.07,.04,.02,.01), n=1200, p.nv=0.12, 0.03) bayes(c(.43,.39), 1200, 0.15, 0.03) # A seguir estão cenários com empate técnico tríplice segundo os institutos de pesquisa. bayes(c(.5813972562, .3158114522, .1027912917), 50) bayes(c(.5144202347, .3246860305, .1608937348), 100) bayes(c(.4160925601, .3316216347, .2522858052), 500) bayes(c(.3919345050, .3324785813, .2755869137), 10^3) bayes(c(.3518464606, .3332479566, .3149055828), 10^4) bayes(c(.3391808234, .3333247966, .3274943799), 10^5) bayes(c(.3333333335, .3333333333, .3333333331), 10^20) ```

filipezabala/desempateTecnico documentation built on Aug. 14, 2021, 2:04 p.m.