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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#> Intervals :
#> Level Percentile BCa
#> 95% ( 1.07, 1.99 ) ( 1.09, 2.05 )
#> Calculations and Intervals on Original Scale
在这里，我们通过设置参数 type = c("perc", "bca") 来选择两个算法，百分位
数算法和 BCa 算法。由此产生的两个估算值显示在其算法名称底部。关于其他算法，请
参阅 boot.ci 函数的帮助页面。
注意，这两种算法给出的置信区间略有不同：（1.068，1.992 ）与（1.086，2.050 ）。 这
令人不安，然而这是使用两种不同算法带来的不可避免的结果。我们不知道如何决定哪
个结果更好。如果选择一种最好的方法对你很重要的话，建议研究相关文档并理解算法
的差异。与此同时，我们能给出的最好建议是，保守地选择最小的下限和最大的上限。
在本例中，那将是区间（1.068，2.050 ）。
默认情况下，boot.ci 函数估计 95% 置信区间。你可以通过 conf 参数进行更改，如下所示：
boot.ci(reps, type = c("perc", "bca"), conf = 0.90)
13.8.4 另请参阅
有关斜率计算，请参阅 13.4 节。关于 Bootstrap 算法的详细教程，可以参考 Bradley
Efron 和 Robert Tib-shirani 的
An Introduction to Bootstrap ...
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