R绘制多样本概率密度分布曲线

概率密度函数可帮助确定随机变量值的较高和较低概率的区域。我们通过密度分布图可以看出数据的整体概貌。

下面主要展示如何用R来绘制多样本概率密度分布曲线

#library
library(tidyverse)
library(viridis)
library(patchwork)
library(ggthemes)


# 加载数据
data <- read.table("probly.csv", header=TRUE, sep=",")
data <- data %>% 
  gather(key="text", value="value") %>%
  mutate(text = gsub("\\.", " ",text)) %>%
  mutate(value = round(as.numeric(value),0))

# 数据注释，包好4个注释和注释的位置坐标
annot <- data.frame(
  text = c("Almost No Chance", "About Even", "Probable", "Almost Certainly"),
  x = c(5, 53, 65, 79),
  y = c(0.15, 0.4, 0.06, 0.1)
)

# 绘制
data %>%
  filter(text %in% c("Almost No Chance", "About Even", "Probable", "Almost Certainly")) %>%
  mutate(text = fct_reorder(text, value)) %>%
  ggplot( aes(x=value, color=text, fill=text)) +
    geom_density(alpha=0.6) +
    scale_fill_viridis(discrete=TRUE) +
    scale_color_viridis(discrete=TRUE) +
    geom_text( data=annot, aes(x=x, y=y, label=text, color=text), hjust=0, size=4.5) +
    theme_few() +
    theme(
      legend.position="none",
      panel.spacing = unit(0.1, "lines"),
      strip.text.x = element_text(size = 8)
    ) +
    xlab("") +
    ylab("Assigned Probability (%)") +
    ggtitle("how people perceive probability vocabulary")

一个简单的多样本概率密度绘制好了

参考资料：

1.https://www.data-to-viz.com/caveat/multi_distribution.html

2.https://support.minitab.com/zh-cn/minitab/18/help-and-how-to/probability-distributions-and-random-data/supporting-topics/basics/using-the-probability-density-function-pdf/