# bayesboot: An Implementation of Rubin's (1981) Bayesian Bootstrap

``````> library(bayesboot)
``````

バージョン: 0.2.0

`as.bayesboot` Coerce to a 'bayesboot' object
`bayesboot` The Bayesian bootstrap
`plot.bayesboot` Plot the result of 'bayesboot'
`plotPost` Graphic display of a posterior probability distribution
`print.bayesboot` Print the first number of draws from the Bayesian bootstrap
`rudirichlet` Produce random draws from a uniform Dirichlet distribution
`summary.bayesboot` Summarize the result of 'bayesboot'

## bayesboot

ベイジアンブーツストラップ

``````> heights <- c(183, 192, 182, 183, 177, 185, 188, 188, 182, 185)
> b1 <- bayesboot(heights, mean)
>
> summary(b1)
``````
``````Bayesian bootstrap

Number of posterior draws: 4000

Summary of the posterior (with 95% Highest Density Intervals):
statistic     mean       sd  hdi.low hdi.high
V1 184.4976 1.153094 182.3595 186.9408

Quantiles:
statistic    q2.5%     q25%   median     q75%  q97.5%
V1 182.2388 183.7409 184.4529 185.2446 186.856

Call:
bayesboot(data = heights, statistic = mean)
``````
``````> # plot(b1)
>
> b2 <- bayesboot(heights, weighted.mean, use.weights = TRUE)
> summary(b2)
``````
``````Bayesian bootstrap

Number of posterior draws: 4000

Summary of the posterior (with 95% Highest Density Intervals):
statistic     mean       sd  hdi.low hdi.high
V1 184.4773 1.188253 182.0777 186.8251

Quantiles:
statistic    q2.5%     q25%   median    q75%   q97.5%
V1 182.0972 183.7012 184.4664 185.257 186.8499

Call:
bayesboot(data = heights, statistic = weighted.mean, use.weights = TRUE)
``````
``````> # plot(b2)
``````

## plotPost

``````> rnorm(1e5, 3, 1) %>% plotPost()
``````

## rudirichlet

``````> set.seed(71)
> rudirichlet(2, 3)
``````
``````           [,1]      [,2]      [,3]
[1,] 0.43594077 0.4264839 0.1375754
[2,] 0.05651936 0.8233262 0.1201545
``````