June 2020
Beginner to intermediate
522 pages
9h 6m
Chinese
Content preview from R 语言经典实例（原书第 2 版）
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13.7.4 另请参阅
使用逻辑回归时，需要根据对残差的解释来判断模型的显著性。我们建议你在尝试从回
归中得出任何结论之前，先查看逻辑回归的相关书籍。
13.8 统计量的 Bootstrap 法
13.8.1 问题
有一个数据集和计算该数据集统计量的函数。现在需要估计统计量的置信区间。
13.8.2 解决方案
使用 boot 包中的 boot 函数来计算统计量的 Bootstrap（自助抽样）：
library(boot)
bootfun <- function(data, indices) {
# . . . calculate statistic using data[indices]. . .
return(statistic)
}
reps <- boot(data, bootfun, R = 999)
这里，参数 data 是原始数据集，可以存储在向量或数据框中。计算统计量的函数（在
本例中为 bootfun）应该有两个参数：data 是原始数据集，indices 是一个整型向量，
它用来从原始数据汇总选择 Bootstrap 样本。
接下来，使用 boot.ci 函数估算自助抽样的置信区间：
boot.ci(reps, type = c("perc", "bca"))
13.8.3 讨论
任何人都可以计算统计量，但他们得到的只是点估计值。我们希望得到一个更高级的估
计。那么什么是置信区间（Confidence Interval，CI）？对于某些统计量，我们可以通过
解析的方式计算置信区间。例如，均值的置信区间由 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.