How to Plot a Smooth Line using GGPlot2

Prerequisites

• Load the ggplot2 package and set the default theme to theme_minimal():

library(ggplot2)
theme_set(
  theme_bw() +
    theme(legend.position = "top")
  )

• Demo dataset:

head(cars)

##   speed dist
## 1     4    2
## 2     4   10
## 3     7    4
## 4     7   22
## 5     8   16
## 6     9   10

Key R function: geom_smooth()

• Key R function: geom_smooth() for adding smoothed conditional means / regression line.
• Key arguments:
  • color, size and linetype: Change the line color, size and type.
  • fill: Change the fill color of the confidence region.

A simplified format of the function `geom_smooth():

geom_smooth(method="auto", se=TRUE, fullrange=FALSE, level=0.95)

Regression line

To add a regression line on a scatter plot, the function geom_smooth() is used in combination with the argument method = lm. lm stands for linear model.

p <- ggplot(cars, aes(speed, dist)) +
  geom_point()
# Add regression line
p + geom_smooth(method = lm)
  
# loess method: local regression fitting
p + geom_smooth(method = "loess")

Loess method for local regression fitting

# loess method: local regression fitting
p + geom_smooth(method = "loess")

Polynomial interpolation

# Remove the confidence bande: se = FALSE
p + geom_smooth(method = "lm", formula = y ~ poly(x, 3), se = FALSE)

Spline interpolation

spline.d <- as.data.frame(spline(cars$speed, cars$dist))
p + geom_line(data = spline.d, aes(x = x, y = y))