r - 使用ggplot2在直方图上绘制置信区间

下面的代码绘制了平均值的采样分布，并计算了20个95％置信区间。如何在直方图中绘制置信区间，如下面的Photoshopped图像所示？

# plot sampling distribution of mean -----------------------------------------------------------
set.seed(1)

population <- rnorm(10000, 3, 3)

population_mean <- mean(population)

my_sample <- sample(population, 100, replace = FALSE)

standard_error <- sqrt(var(my_sample)/length(my_sample))

sampling_distribution_of_mean <- rnorm(10000, mean = population_mean, sd = standard_error)

library(ggplot2)
ggplot(data.frame(x = sampling_distribution_of_mean), aes(x)) + geom_histogram() + geom_vline(xintercept = population_mean, color = "red")


# calculate 20 lots of 95% confidence intervals -----------------------------------------------------------

my_confidence_intervals <- function(){

    my_sample <- sample(population, 100, replace = FALSE)

    sample_mean <- mean(my_sample)

    standard_error <- sqrt(var(my_sample)/length(my_sample))

    margin_of_error <- 1.96*standard_error

    mean_minus_margin_of_error <- sample_mean - margin_of_error
    mean_plus_margin_of_error <- sample_mean + margin_of_error

    c(mean_minus_margin_of_error, mean_plus_margin_of_error)

}

library(plyr)
llply(1:20, function(x) my_confidence_intervals())

最佳答案

您可能要构建一个包含间隔的data.frame，然后添加一层水平误差线以绘制它们。首先，我将范围转换为data.frame

xx<-llply(1:20, function(x) my_confidence_intervals())
xx<-data.frame(y=1:20*50, x=do.call(rbind, xx))

现在我将它们添加到情节中

ggplot(data.frame(x = sampling_distribution_of_mean), aes(x)) +
    geom_histogram() +
    geom_vline(xintercept = population_mean, color = "red") +
    geom_errorbarh(aes(y=y, x=x.1, xmin=x.1, xmax=x.2), data=xx, col="#0094EA", size=1.2)

这使

请注意，在创建data.frame时，我为每个范围明确设置了y值。

关于r - 使用ggplot2在直方图上绘制置信区间，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/31191167/