A small little idea on implementing bootstrap only using purrr, not dplyr based, after reading a google data science blog

pure_purrr_boot.R

## http://www.unofficialgoogledatascience.com/2015/08/an-introduction-to-poisson-bootstrap26.html

n <- 10000000
data <- rnorm(n, mean = 4, sd = 2)

matrix_col_as_vector <- . %>% as.list() %>% purrr::as_vector()

boot_delta_mean <- function(id, data){
	mean_data <- mean(data)
	indicator <- 
		rmultinom(n = 1, size = n, prob = rep(1/n, n)) %>% 
		matrix_col_as_vector()
	as.numeric((indicator %*% data)/n) - mean_data
}

purrr::map_dbl(1:20, .f = ~ boot_delta_mean(. , data)) %>% 
	quantile(., probs = c(0.1, 0.9)) %>% 
	purrr::map_dbl(~ mean(data) + .)