r - ggplot2:多密度图与父直方图分布不匹配-6ren

r - ggplot2:多密度图与父直方图分布不匹配

转载作者：行者123 更新时间：2023-12-01 13:37:54

我有兴趣创建一个由叠加了两个密度图的直方图组成的图。这些密度图由来自父直方图分布的点组成。我想看到的就像在 this 问题中看到的情节 - 查看产生红色和绿色分布的答案。

这是我的数据:

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1430L, 3189L, 2538L, 2733L, 1947L, 3371L, 1867L, 1248L, 2994L, 
2418L, 490L, 65L, 578L, 3945L, 3688L, 1018L, 4079L, 1474L, 876L, 
3916L, 639L, 1624L, 1056L, 3571L, 3394L, 2604L, 92L, 414L, 1357L, 
4058L, 3403L, 1479L, 3148L, 1112L, 3249L, 3161L, 213L, 3116L, 
3259L, 1898L, 2257L, 1519L, 3949L, 1205L, 1722L, 2788L, 1177L, 
545L, 2347L, 1410L, 3020L, 3999L, 2452L, 1918L, 1507L, 3357L, 
3135L, 3029L, 740L, 3201L, 2355L, 1828L, 2851L, 1666L, 935L, 
1885L, 1072L, 1669L, 1781L, 3390L, 3267L, 1881L, 3995L, 1900L, 
897L, 597L, 1138L, 3366L, 572L, 3855L, 524L, 3793L, 705L, 68L, 
1551L, 1592L, 2344L, 1548L, 1650L, 1026L, 225L, 3969L, 3551L, 
2298L, 837L, 456L, 4085L, 2261L, 372L, 844L, 3621L, 1719L, 2007L, 
3691L, 1252L, 3383L, 3590L, 406L, 2805L, 195L, 2212L, 2018L, 
212L, 1143L, 2294L, 941L, 982L, 1691L), class = "data.frame")

我试图通过创建指示子分布成员资格的新数据框来模仿上面答案中的情节。将上面的数据分配给变量dat。

library(ggplot2)

g1 <- dat[dat$Filter == "Signal", ]
g2 <- dat[dat$Filter == "Background", ]

ggplot(dat, aes(x = Cutoff)) +
  geom_histogram(aes(y = ..density..), fill = "grey60", bins = 100) +
  stat_function(fun = dnorm,
                args = list(mean = mean(g1$Cutoff),
                            sd = sd(g1$Cutoff)),
                geom = "density",
                fill = "chartreuse3",
                alpha = 0.5) +
  stat_function(fun = dnorm,
                args = list(mean = mean(g2$Cutoff),
                            sd = sd(g2$Cutoff)),
                geom = "density",
                fill = "firebrick2",
                alpha = 0.5) +
  theme_bw()

但是，我从中得到的情节是这样的:

虽然密度图遵循直方图的一般形状，但红色峰值看起来比直方图高很多。那么，我是否误解了关于密度图和直方图有何不同的基本知识？它们完全在不同的 y 轴刻度上吗？我如何更改我的比例以使生成的图看起来更接近上面链接的 StackOverflow 答案中的示例？请注意，在我包含 5000 个观测值的实际数据集中，红色峰值看起来更加明显，远远超过直方图的限制。弄乱垃圾箱有一点帮助，但作用不大。

最佳答案

首先，我认为您是根据每个子集的均值和标准差绘制完美的正态分布，而不是实际的密度分布。其次，您正在绘制基于 500 个观测值的密度直方图，然后绘制基于 328 和 172 个观测值的两条密度曲线。尝试添加两个单独的 geom_histogram 和 geom_density 层来指定每个子集...

ggplot(dat, aes(x = Cutoff)) +
  geom_histogram(data=dat[which(dat$Filter%in%"Signal"),], aes(y = ..density..), fill = "grey60", bins = 100) +
  geom_histogram(data=dat[which(dat$Filter%in%"Background"),], aes(y = ..density..), fill = "grey60", bins = 100) +
  geom_density(data=dat[which(dat$Filter%in%"Signal"),], aes(x=Cutoff, y=..density..), fill="chartreuse3", alpha=0.5) +
  geom_density(data=dat[which(dat$Filter%in%"Background"),], aes(x=Cutoff, y=..density..), fill="firebrick2", alpha=0.5) +
  theme_bw()

...会给你这个情节:

否则，如果您确实想要绘制单个父直方图但绘制多个子集密度，您应该期望峰值不匹配。即:

ggplot(dat, aes(x = Cutoff)) +
  geom_histogram(aes(y = ..density..), fill = "grey60", bins = 100) +
  geom_density(data=dat[which(dat$Filter%in%"Signal"),], aes(x=Cutoff, y=..density..), fill="chartreuse3", alpha=0.5) +
  geom_density(data=dat[which(dat$Filter%in%"Background"),], aes(x=Cutoff, y=..density..), fill="firebrick2", alpha=0.5) +
  theme_bw()

关于r - ggplot2:多密度图与父直方图分布不匹配，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/42491473/

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r - ggplot2:多密度图与父直方图分布不匹配