Letter-Value Plots: Boxplots for Large Data
Letter-Value Plots: Boxplots for Large Data
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DOI：
10.1080/10618600.2017.1305277
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发表时间：
2017-01-01
影响因子：
2.4
通讯作者：
Kafadar, Karen
中科院分区：
文献类型：
--
作者：
Hofmann, Heike;Wickham, Hadley;Kafadar, Karen
箱形图是有用的显示，它传达了有关变量分布的粗略信息。箱形图设计为手工绘制，最适合小型数据集，其中超过四分位数的尾部行为的详细估计可能不可信。更大的数据集提供了对尾部行为更精确的估计，但箱形图并没有利用这种精确度，而是呈现了大量的极端，尽管不是意外的观察结果。字母值图通过使用“字母值”（Tukey定义的顺序统计量）包含有关尾部的更详细信息来解决这个问题。箱形图显示前两个字母值（中位数和四分位数）;字母值图显示进一步的字母值，只要它们是相应分位数的可靠估计值。我们用真实的数据说明了字母值图，证明了它们对大型数据集的有用性。所有图形都是使用R软件包lvplot创建的，代码和数据可在补充材料中获得。
Boxplots are useful displays that convey rough information about the distribution of a variable. Boxplots were designed to be drawn by hand and work best for small datasets, where detailed estimates of tail behavior beyond the quartiles may not be trustworthy. Larger datasets afford more precise estimates of tail behavior, but boxplots do not take advantage of this precision, instead presenting large numbers of extreme, though not unexpected, observations. Letter-value plots address this problem by including more detailed information about the tails using "letter values," an order statistic defined by Tukey. Boxplots display the first two letter values (the median and quartiles); letter-value plots display further letter values so far as they are reliable estimates of their corresponding quantiles. We illustrate letter-value plots with real data that demonstrate their usefulness for large datasets. All graphics are created using the R package lvplot, and code and data are available in the supplementary materials.