ChauBoxplot and AdaptiveBoxplot: two R packages for boxplot-based outlier detection

Tiejun Tong

doi:10.1080/24754269.2026.2642439

ChauBoxplot and AdaptiveBoxplot: two R packages for boxplot-based outlier detection

2026-03-01

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DOI：10.1080/24754269.2026.2642439

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Tukey's boxplot is widely used for outlier detection; however, its classic fixed-fence rule tends to flag an excessive number of outliers as the sample size grows. To address this, we introduce two new R packages, ChauBoxplot and AdaptiveBoxplot, which implement more robust and statistically principled outlier detection methods. We illustrate their advantages and practical implications through comprehensive simulation studies and a real-world analysis of provincial university admission rates from China's National College Entrance Examination. Based on these findings, we provide practical guidance to help practitioners select appropriate boxplot methods, achieving a balance between interpretability and statistical reliability.

Keywords:

Box-and-whisker plot

Chauvenet's criterion

Chauvenet-type boxplot

fence coefficient

outlier detection

sample size

ChauBoxplot and AdaptiveBoxplot: two R packages for boxplot-based outlier detection

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