# data
set.seed (123)
xvar <- c(rnorm (1000, 50, 30), rnorm (1000, 40, 10), rnorm (1000, 70, 10))
yvar <- xvar + rnorm (length (xvar), 0, 20)
myd <- data.frame (xvar, yvar)
# density plot for xvar
upperp = 80 # upper cutoff
lowerp = 30 # lower cutoff
x <- myd$xvar
plot(density(x))
dens <- density(x)
x11 <- min(which(dens$x <= lowerp))
x12 <- max(which(dens$x <= lowerp))
x21 <- min(which(dens$x > upperp))
x22 <- max(which(dens$x > upperp))
with(dens, polygon(x = c(x[c(x11, x11:x12, x12)]),
y = c(0, y[x11:x12], 0), col = "green"))
with(dens, polygon(x = c(x[c(x21, x21:x22, x22)]),
y = c(0, y[x21:x22], 0), col = "red"))
abline(v = c(mean(x)), lwd = 2, lty = 2, col = "red")
# density plot with yvar
upperp = 70 # upper cutoff
lowerp = 30 # lower cutoff
x <- myd$yvar
plot(density(x))
dens <- density(x)
x11 <- min(which(dens$x <= lowerp))
x12 <- max(which(dens$x <= lowerp))
x21 <- min(which(dens$x > upperp))
x22 <- max(which(dens$x > upperp))
with(dens, polygon(x = c(x[c(x11, x11:x12, x12)]),
y = c(0, y[x11:x12], 0), col = "green"))
with(dens, polygon(x = c(x[c(x21, x21:x22, x22)]),
y = c(0, y[x21:x22], 0), col = "red"))
abline(v = c(mean(x)), lwd = 2, lty = 2, col = "red")
我需要绘制双向密度图,不确定是否有比以下方法更好的方式:
ggplot(myd,aes(x=xvar,y=yvar))+
stat_density2d(aes(fill=..level..), geom="polygon") +
scale_fill_gradient(low="blue", high="green") + theme_bw()
我希望将所有三种类型合并成一个(我不知道是否可以在ggplot中创建双向图),无论解决方案是使用ggplot还是base或混合。考虑到R的稳健性,我希望这是可行的项目。我个人更喜欢ggplot2。 注意:此图中的较低阴影不正确,红色应始终较低,绿色应较高在xvar和yvar图中,对应于xy密度图中的阴影区域。
编辑:图表的最终期望(感谢seth和jon提供非常接近的答案) (1)去除空格和轴刻度标签等,使其紧凑 (2)网格的对齐,使中间图的刻度和网格与侧面的刻度和标签对齐,并且图形的大小看起来相同。