将点连接到绘图中的回归线 [英] Connecting points to regression line in plot

问题描述

考虑 ISLR书中的以下数据：

 收入< - 结构（列表（X = 1:30，Education = c（10，10.4013377926421，
 10.8428093645485，11.2441471571906， 11.6454849498328，12.0869565217391，
 12.4882943143813，12.8896321070234，13.2909698996656，13.7324414715719，
 14.133779264214，14.5351170568562，14.9765886287625，15.3779264214047，
 15.7792642140468，16.2207357859532，16.6220735785953，17.0234113712375，
 17.4648829431438，17.866220735786，18.2675585284281， 18.7090301003344，
 19.1103678929766，19.5117056856187，19.9130434782609，20.3545150501672，
 20.7558528428094，21.1571906354515，21.5986622073579，22），收入= C（26.6588387834389，
 27.3064353457772，22.1324101716143，21.1698405046065，15.1926335164307，
 26.3989510407284 ，17.435306578572,25.5078852305278,36.884594694235，
 39.666108747637,34.3962805641312,41.4979935356871， 44.9815748660704，
 47.039595257834，48.2525782901863，57.0342513373801，51.4909192102538，
 61.3366205527288，57.581988179306，68.5537140185881，64.310925303692，
 68.9590086393083，74.6146392793647，71.8671953042483，76.098135379724，
 75.77521802986，72.4860553152424，77.3550205741877，72.1187904524136， 
 80.2605705009016）），.Names = c（X，Education，Income），class =data.frame，row.names = c（NA，
 -30L）） 
  

我想重现它们的图形，它将点连接到回归线来表示误差项，那就是：

p>

很容易用 ggplot2 绘制点和回归线：

  ggplot（收入，aes（教育，收入））+ geom_point（color =red）+ geom_smooth（se = FALSE）
  

但我想不出一种简单的方法来连接poi nts到像他们那样的回归线。

有没有一种简单的方法可以做到这一点（使用 base ， ggplot2 或格子）？

解决方案

h3>

  require（ggplot2）
 
 mod < - 黄土（收入〜教育，数据=收入） 
收入<  - 转型（收入，拟合=拟合（mod））
  

ggplot版本

  ggplot（收入，aes（教育，收入））+ 
 geom_point（color =red）+ 
 geom_smooth（se = FALSE，method =loess）+ 
 geom_segment（aes（x = Education，y = Income，
 xend = Education，yend = Fitted））
  

基本图形版本

  plot（Income = Education，data = Income，type =p，col =red，
 cex = 1.25）
 points（Fitted〜Education，data = Income）
 lines （Fitted〜Education，data = Income，col =blue）
 with（Income，segments（Education，Income，Educat ）
 $ / code> 

根据您的审美需求进行相应调整。

Consider the following data from the ISLR book:

Income <- structure(list(X = 1:30, Education = c(10, 10.4013377926421, 
10.8428093645485, 11.2441471571906, 11.6454849498328, 12.0869565217391, 
12.4882943143813, 12.8896321070234, 13.2909698996656, 13.7324414715719, 
14.133779264214, 14.5351170568562, 14.9765886287625, 15.3779264214047, 
15.7792642140468, 16.2207357859532, 16.6220735785953, 17.0234113712375, 
17.4648829431438, 17.866220735786, 18.2675585284281, 18.7090301003344, 
19.1103678929766, 19.5117056856187, 19.9130434782609, 20.3545150501672, 
20.7558528428094, 21.1571906354515, 21.5986622073579, 22), Income = c(26.6588387834389, 
27.3064353457772, 22.1324101716143, 21.1698405046065, 15.1926335164307, 
26.3989510407284, 17.435306578572, 25.5078852305278, 36.884594694235, 
39.666108747637, 34.3962805641312, 41.4979935356871, 44.9815748660704, 
47.039595257834, 48.2525782901863, 57.0342513373801, 51.4909192102538, 
61.3366205527288, 57.581988179306, 68.5537140185881, 64.310925303692, 
68.9590086393083, 74.6146392793647, 71.8671953042483, 76.098135379724, 
75.77521802986, 72.4860553152424, 77.3550205741877, 72.1187904524136, 
80.2605705009016)), .Names = c("X", "Education", "Income"), class = "data.frame", row.names = c(NA, 
-30L))

I want to reproduce their plot, which connects the points to the regression line to represent the error term, that is:

It is easy to plot the points and the regression line with ggplot2:

ggplot(Income, aes(Education, Income)) + geom_point(color="red")+geom_smooth(se=FALSE)

But I could not think of an easy way to connect the points to the regression line like they did.

Is there an easy way do it (with either base, ggplot2 or lattice)?

解决方案

Prelim code

require("ggplot2")

mod <- loess(Income ~ Education, data = Income)
Income <- transform(Income, Fitted = fitted(mod))

ggplot version

ggplot(Income, aes(Education, Income)) + 
  geom_point(color="red") + 
  geom_smooth(se=FALSE, method = "loess") +
  geom_segment(aes(x = Education, y = Income,
                   xend = Education, yend = Fitted))

base graphics version

plot(Income ~ Education, data = Income, type = "p", col = "red",
     cex = 1.25)
points(Fitted ~ Education, data = Income)
lines(Fitted ~ Education, data = Income, col = "blue")
with(Income, segments(Education, Income, Education, Fitted))

Adjust accordingly to suit your aesthetic needs.

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