R:置信区间由ggplot2部分显示(使用geom_smooth()) [英] R : confidence interval being partially displayed with ggplot2 (using geom_smooth())

问题描述

我有以下简单的R代码:

I have the following simple R code:

disciplines <- c("A","C","B","D","E")
# To stop ggplot from imposing alphabetical ordering on x-axis
disciplines <- factor(disciplines, levels=disciplines, ordered=T)

d1 <- c(0.498, 0.521, 0.332, 0.04, 0.04)
d2 <- c(0.266, 0.202, 0.236, 0.06, 0.06)
d3 <- c(0.983, 0.755, 0.863, 0.803, 0.913)
d4 <- c(0.896, 0.802, 0.960, 0.611, 0.994)

df <- data.frame(disciplines, d1, d2, d3, d4)
df.m <- melt(df)
graph <- ggplot(df.m, aes(group=1,disciplines,value,colour=variable,shape=variable)) +
         geom_point() +
         geom_smooth(stat="smooth", method=loess, level=0.95) +
         scale_x_discrete(name="Disciplines") +
         scale_y_continuous(limits=c(-1,1), name="Measurement")

输出看起来像这样:

The output looks like this:

为什么没有在整个曲线上显示置信区间?

Why does the confidence interval not display along the entire curve?

注意:

1. 我不想使用fullrange=TRUE，因为那样只会产生一条蓝色的直线，而不是当前输出中的锯齿形.
2. 我正在将该图与另一个在(0，-1]范围内具有负值的图进行比较，这就是y轴具有limits=c(-1,1))的原因

1. I don't want to have fullrange=TRUE because that just yields a single straight blue line instead of the zigzag shape in the current output.
2. I am comparing this plot with another plot which has negative values in the (0,-1] range, which is why the y-axis has limits=c(-1,1))

推荐答案

对于置信区间的前三个分段，范围的顶端至少部分超出范围(范围为[-1，1] ，而不是轴上稍微扩大的范围). ggplot的默认行为是不显示部分超出范围的任何对象.您可以通过在scale_y_continuous中添加oob=scales::rescale_none来解决此问题:

For the first three segments of the confidence interval, the top end of the range is at least partially out of bounds (the bounds being [-1, 1], not the slightly expanded range on the axes). ggplot's default behavior is to not display any object that is partially out of bounds. You can fix this by adding oob=scales::rescale_none to scale_y_continuous:

library(scales)
graph <- ggplot(df.m, aes(group=1,disciplines,value,colour=variable,shape=variable)) +
         geom_point() +
         geom_smooth(stat="smooth", method=loess, level=0.95) +
         scale_x_discrete(name="Disciplines") +
         scale_y_continuous(limits=c(-1,1), name="Measurement", oob=rescale_none)

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