拟合Gamma分布并在R中按因子绘图

Question

我有带有数字列数量和分类列欺诈的data.frame对象：

amount <- [60.00, 336.38, 119.00, 115.37, 220.01, 60.00, 611.88, 189.78 ...]

fraud <- [1,0,0,0,0,0,1,0, ...]

我想拟合一个伽马分布来求和，但要按factor(fraud)绘制它。 我想要一个图表，该图表将显示2条具有2种不同颜色的曲线，以区分2组（欺诈/非欺诈组）。

到目前为止，这是我所做的：

fit.gamma1 <- fitdist(df$amount[df$fraud == 1], distr = "gamma", method = "mle")
plot(fit.gamma1)

fit.gamma0 <- fitdist(df$amount[df$fraud == 0], distr = "gamma", method = "mle")
plot(fit.gamma0)

我使用了以下参考： 如何将R数据中的伽马分布拟合？

Answer 1

也许你想要的是

curve(dgamma(x, shape = fit.gamma0$estimate[1], rate = fit.gamma0$estimate[2]), 
      from = min(amount), to = max(amount), ylab = "")
curve(dgamma(x, shape = fit.gamma1$estimate[1], rate = fit.gamma1$estimate[2]), 
      from = min(amount), to = max(amount), col = "red", add = TRUE)

或与ggplot2

ggplot(data.frame(x = range(amount)), aes(x)) + 
  stat_function(fun = dgamma, aes(color = "Non fraud"),
                args = list(shape = fit.gamma0$estimate[1], rate = fit.gamma0$estimate[2])) +
  stat_function(fun = dgamma, aes(color = "Fraud"),
                args = list(shape = fit.gamma1$estimate[1], rate = fit.gamma1$estimate[2])) +
  theme_bw() + scale_color_discrete(name = NULL)