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R 语言经典实例(原书第 2 版)
book

R 语言经典实例(原书第 2 版)

by J.D. Long, Paul Teetor
June 2020
Beginner to intermediate
522 pages
9h 6m
Chinese
China Machine Press
Content preview from R 语言经典实例(原书第 2 版)
统计概论
231
FALSE 1 表示 TRUE 所有 1 0 的平均值就是 vec 中小于
x
的值的比例,或
x
逆分位数。
9.6.4 另请参阅
这是 9.2 节中描述的方法的一个应用。
9.7 数据转换为
z
分数
9.7.1 问题
你有一个数据集,需要计算所有数据元素的相应
z
分数。(又称为
规范化
数据。)
9.7.2 解决方案
调用函数 scale
scale(x)
#> [,1]
#> [1,] 0.8701
#> [2,] -0.7133
#> [3,] -1.0503
#> [4,] 0.5790
#> [5,] -0.6324
#> [6,] 0.0991
#> [7,] 2.1495
#> [8,] 0.2481
#> [9,] -0.8155
#> [10,] -0.7341
#> attr(,"scaled:center")
#> [1] 2.42
#> attr(,"scaled:scale")
#> [1] 2.11
这个方法适用于向量、矩阵和数据框。 在向量的情况下,scale 返回规范化值的向量。
在矩阵和数据框的情况下,scale 独立地对每一列进行规范化,并在矩阵中返回规范化
值的列。
9.7.3 讨论
你可能还需要对单一值 y 相对于数据集 x 进行规范化,这可以通过使用向量化运算
进行:
(y - mean(x)) / sd(x)
#> [1] -0.633
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Publisher Resources

ISBN: 9787111656814