The R Package Ecosystem for Robust Statistics

被引：0

作者：

Todorov, Valentin ^{[1
]}

机构：

[1] United Nations Industrial Development Organization (UNIDO), Vienna, Austria

来源：

Wiley Interdisciplinary Reviews: Computational Statistics | 2024年 / 16卷 / 06期

关键词：

In the last few years; the number of R packages implementing different robust statistical methods have increased substantially. There are now numerous packages for computing robust multivariate location and scatter; robust multivariate analysis like principal components and discriminant analysis; robust linear models; and other algorithms dedicated to cope with outliers and other irregularities in the data. This abundance of package options may be overwhelming for both beginners and more experienced R users. Here we provide an overview of the most important 25 R packages for different tasks. As metrics for the importance of each package; we consider its maturity and history; the number of total and average monthly downloads from CRAN (The Comprehensive R Archive Network); and the number of reverse dependencies. Then we briefly describe what each of these package does. After that we elaborate on the several above-mentioned topics of robust statistics; presenting the methodology and the implementation in R and illustrating the application on real data examples. Particular attention is paid to the robust methods and algorithms suitable for high-dimensional data. The code for all examples is accessible on the GitHub repository https://github.com/valentint/robust-R-ecosystem-WIREs. © 2024 Wiley Periodicals LLC;

D O I：

10.1002/wics.70007

中图分类号：

学科分类号：

摘要：

引用

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