ChauBoxplot is an R package designed to create an
improved version of the boxplot. This package implements a new fence
coefficient proposed by Lin et al. (2025), replacing the traditional
fence coefficient \(k=1.5\) in Tukey’s
boxplot. The new coefficient \(k=k_n^{Chau}\) is calculated based on
Chauvenet’s criterion, which is given in formula (9) in their paper.
base R. Its usage is similar to boxplot(), but it employs
an updated fence coefficient for more robust outlier detection.ggplot2, functioning similarly to geom_boxplot().To install the ChauBoxplot package from CRAN, please use
the following command in R:
install.packages(“ChauBoxplot”)
To install the ChauBoxplot package from GitHub, please
use the following commands in R:
library(devtools)
install_github(“tiejuntong/ChauBoxplot”)
For detailed documentation and usage examples, please also visit the package website at https://github.com/tiejuntong/ChauBoxplot/.
Below is a real example with R code of how to create a Chauvenet-type boxplot for the pay adjustment rates of senior civil servants in Hong Kong.
library(ChauBoxplot)
rate.senior <- c(4.96, 6.30, -5.38, 1.60, 7.24, 5.26, 2.55, 5.96,
3.96, 4.19, 1.88, 4.06, 4.75, 0, 0, 2.5, 2.87, 3.00)/100
chau_boxplot(rate.senior)
library(ggplot2)
library(ChauBoxplot)
rate.senior <- c(4.96, 6.30, -5.38, 1.60, 7.24, 5.26, 2.55, 5.96,
3.96, 4.19, 1.88, 4.06, 4.75, 0, 0, 2.5, 2.87, 3.00)/100
year <- 2007:2024
data.senior <- data.frame(x=year, y=rate.senior)
C.boxplot.senior <-
ggplot(data.senior, aes(y=rate.senior)) +
geom_chau_boxplot(fill=“purple”,width=3) +
theme(legend.position = “none”) +
scale_x_discrete(breaks = NULL) +
ylim(-0.057,0.077) +
theme(plot.margin = unit(c(0, 0, 0, 0), “inches”)) +
labs(title=“C.boxplot”, subtitle=“Senior civil servants”, x=““,
y=”“)
print(C.boxplot.senior)
Hongmei Lin, Riquan Zhang and Tiejun Tong (2025). When Tukey meets Chauvenet: a new boxplot criterion for outlier detection. Journal of Computational and Graphical Statistics, accepted.
Should you have any questions, please feel free to contact Tiejun Tong via tongt@hkbu.edu.hk.