用R对线性回归进行现代的介绍

Albert Y. Kim, Chester Ismay, M. Kuhn
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引用次数: 2

摘要

我们提出了现代R数据集和函数包,用于方便使用的入门线性回归(Wickham,Averick,et al.,2019)。这些工具利用完善的tidyverse和扫帚包来促进1)使用包括置信区间的回归表,2)访问观测水平上的回归输出(例如拟合/预测值和残差),3)检查回归拟合的标量摘要(例如R、R adj和均方误差),以及4)使用类似ggplot2的语法可视化平行斜率回归模型(Robinson&Hayes,2019;Wickham,Chang等人,2019)。该R包旨在补充《通过数据科学进行统计推断:R与潮汐的现代划分》一书(Ismay&Kim,2019)。请注意,这本书也可在线访问https://moderndive.com简称“ModernDive”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Take a moderndive into introductory linear regression with R
We present the moderndive R package of datasets and functions for tidyverse-friendly introductory linear regression (Wickham, Averick, et al., 2019). These tools leverage the well-developed tidyverse and broom packages to facilitate 1) working with regression tables that include confidence intervals, 2) accessing regression outputs on an observation level (e.g. fitted/predicted values and residuals), 3) inspecting scalar summaries of regression fit (e.g. R, R adj , and mean squared error), and 4) visualizing parallel slopes regression models using ggplot2-like syntax (Robinson & Hayes, 2019; Wickham, Chang, et al., 2019). This R package is designed to supplement the book “Statistical Inference via Data Science: A ModernDive into R and the Tidyverse” (Ismay & Kim, 2019). Note that the book is also available online at https://moderndive.com and is referred to as “ModernDive” for short.
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