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arXiv · 2601.13759

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

Tiejun Tong·Hongmei Lin·Bowen Gang·Riquan Zhang
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Abstract

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.

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Tiejun Tong, Hongmei Lin, Bowen Gang, Riquan Zhang. 2026-01-20. ChauBoxplot and AdaptiveBoxplot: Two R packages for boxplot-based outlier detection. https://arxiv.org/abs/2601.13759

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