有沒有辦法使用 R 來打破圖表軸並打破線性回歸線？

Question

我試圖弄清楚如何修改一個散點圖，該散點圖包含沿由大間隙分隔的連續體的兩組數據。 該圖需要在 x 軸和回歸線上中斷。

這段使用 ggplot2 庫的 R 代碼准確地呈現了數據，但由於圖形上有大量空白空間而難看。 皮爾遜相關系數為 -0.1380438。

library(ggplot2)
p <- ggplot(, aes(x = dis, y = result[, 1])) + geom_point(shape = 1) +
  xlab("X-axis") +
  ylab("Y-axis") + geom_smooth(color = "red", method = "lm", se = F) + theme_classic()
p + theme(plot.title = element_text(hjust = 0.5, size = 14))

此 R 代碼使用 gap.plot 來生成所需的中斷，但回歸線不包含中斷並且不能正確反映斜率。 正如您所看到的，回歸線的斜率不像上圖那樣尖銳，並且這些不同組之間的線的斜率需要有明顯的區別。

library(plotrix)
gap.plot(
  x = dis,
  y = result[, 1],
  gap = c(700, 4700),
  gap.axis = "x",
  xlab = "X-Axis",
  ylab = "Y-Axis",
  xtics = seq(0, 5575, by = 200)
)
abline(v = seq(700, 733) , col = "white") 
abline(lm(result[, 1] ~ dis), col = "red", lwd = 2)
axis.break(1, 716, style = "slash")               

使用MS畫圖，我創建的圖形應該是什么樣子的近似值。 請注意頂部的斷點以及兩組之間回歸線上的不連續性。

Answer 1

一種解決方案是將回歸線分成兩部分繪制，使用ablineclip限制每次繪制的內容。 （類似於@tung 的建議，盡管很明顯您想要單個圖形的外觀而不是小平面的外觀。）這是如何工作的：

library(plotrix)

# Simulate some data that looks roughly like the original graph.
dis = c(rnorm(100, 300, 50), rnorm(100, 5000, 100))
result = c(rnorm(100, 0.6, 0.1), rnorm(100, 0.5, 0.1))

# Store the location of the gap so we can refer to it later.
x.axis.gap = c(700, 4700)

# gap.plot() works internally by shifting the location of the points to be
# plotted based on the gap size/location, and then adjusting the axis labels
# accordingly.  We'll re-compute the second half of the regression line in the
# same way; these are the new values for the x-axis.
dis.alt = dis - x.axis.gap[1]

# Plot (same as before).
gap.plot(
  x = dis,
  y = result,
  gap = x.axis.gap,
  gap.axis = "x",
  xlab = "X-Axis",
  ylab = "Y-Axis",
  xtics = seq(0, 5575, by = 200)
)
abline(v = seq(700, 733), col = "white")
axis.break(1, 716, style = "slash")

# Add regression line in two pieces: from 0 to the start of the gap, and from
# the end of the gap to infinity.
ablineclip(lm(result ~ dis), col = "red", lwd = 2, x2 = x.axis.gap[1])
ablineclip(lm(result ~ dis.alt), col = "red", lwd = 2, x1 = x.axis.gap[1] + 33)