我有一个问题,了解如何正确使用dplyr
bootstrap
功能。
我想要的是从两个随机分配的组生成一个bootstrap分布,并计算平均值的差异,例如:
library(dplyr)
library(broom)
data(mtcars)
mtcars %>%
mutate(treat = sample(c(0, 1), 32, replace = T)) %>%
group_by(treat) %>%
summarise(m = mean(disp)) %>%
summarise(m = m[treat == 1] - m[treat == 0])
问题是我需要重复此操作100
,1000
或更多次。
使用replicate
,我可以
frep = function(mtcars) mtcars %>%
mutate(treat = sample(c(0, 1), 32, replace = T)) %>%
group_by(treat) %>%
summarise(m = mean(disp)) %>%
summarise(m = m[treat == 1] - m[treat == 0])
replicate(1000, frep(mtcars = mtcars), simplify = T) %>% unlist()
并获得分发
我真的不知道如何在这里使用bootstrap
。我应该怎么开始?
mtcars %>%
bootstrap(10) %>%
mutate(treat = sample(c(0, 1), 32, replace = T))
mtcars %>%
bootstrap(10) %>%
do(tidy(treat = sample(c(0, 1), 32, replace = T)))
它并没有真正起作用。我应该在哪里放bootstrap
点?
感谢。
答案 0 :(得分:2)
在do
步骤中,我们使用data.frame
打包并创建'处理'专栏,然后我们可以按“复制”进行分组。并且'对待'获取summarise
d输出列
mtcars %>%
bootstrap(10) %>%
do(data.frame(., treat = sample(c(0,1), 32, replace=TRUE))) %>%
group_by(replicate, treat) %>%
summarise(m = mean(disp)) %>%
summarise(m = m[treat == 1] - m[treat == 0])
#or as 1 occurs second and 0 second, we can also use
#summarise(m = last(m) - first(m))