是否可以在R中的ggplot中重新创建bayesplot的“ mcmc_areas”图的功能

这是一个生成类似于的图的函数bayesplot::mcmc_areas。它以可选的间隔概率宽度设置来绘制可信间隔（默认为相等，或最高密度）：

library(tidyverse)
library(ggridges)
library(bayestestR)
theme_set(theme_classic(base_size=15))

# Create ridgeplots with credible intervals
# ARGUMENTS
# data A data frame
# FUN A function that calculates credible intervals
# ci The width of the credible interval
# ... For passing optional arguments to geom_ridgeline. 
#      For example, change the scale parameter to control overlap of ridge lines. 
#      geom_ridgeline's default is scale=1.
plot_density_ridge = function(data, FUN=c("eti", "hdi"), ci=0.89, ...) {
  
  # Determine whether to use eti or hdi function
  FUN = match.arg(FUN)
  FUN = match.fun(FUN)
  
  # Get kernel density estimate as a data frame
  dens = map_df(data, ~ {
    d = density(.x, na.rm=TRUE)
    tibble(x=d$x, y=d$y)
  }, .id="name")
  
  # Set relative width of median line
  e = diff(range(dens$x)) * 0.006
  
  # Get credible interval width and median
  cred.int = data %>% 
    pivot_longer(cols=everything()) %>% 
    group_by(name) %>% 
    summarise(CI=list(FUN(value, ci=ci)),
              m=median(value, na.rm=TRUE)) %>% 
    unnest_wider(CI)
  
  dens %>% 
    left_join(cred.int) %>% 
    ggplot(aes(y=name, x=x, height=y)) +
      geom_vline(xintercept=0, colour="grey70") +
      geom_ridgeline(data= . %>% group_by(name) %>%
                       filter(between(x, CI_low, CI_high)),
                     fill=hcl(230,25,85), ...) +
      geom_ridgeline(data=. %>% group_by(name) %>% 
                       filter(between(x, m - e, m + e)),
                     fill=hcl(240,30,60), ...) +
      geom_ridgeline(fill=NA, ...) + 
      geom_ridgeline(fill=NA, aes(height=0), ...) +
      labs(y=NULL, x=NULL)
  
}

现在让我们尝试一下功能

# Fake data
set.seed(2)
d = data.frame(a = rnorm(1000, 0.6, 1),
               b = rnorm(1000, 1.3, 0.5),
               c = rnorm(1000, -1.2, 0.7))

plot_density_ridge(d)
plot_density_ridge(d, ci=0.5, scale=1.5)
plot_density_ridge(iris %>% select(-Species)) 
plot_density_ridge(iris %>% select(-Species), FUN="hdi")