R语言：3维数组数据的计算机协方差矩阵 数据

编程问答 2022-06-06

问题描述

如何在虹膜数据集（3-d数组数据集）上的r中使用apply（）函数来计算变量的间隔长度，间隔宽度，花瓣长度和花瓣宽度的协方差矩阵 Setosa，Versicolor和Virginica这3个物种中的每一个均以3维数组表示。

这是数据集的前6行

,Setosa
      Sepal L. Sepal W. Petal L. Petal W.
[1,]      5.1      3.5      1.4      0.2
[2,]      4.9      3.0      1.4      0.2
[3,]      4.7      3.2      1.3      0.2
[4,]      4.6      3.1      1.5      0.2
[5,]      5.0      3.6      1.4      0.2
[6,]      5.4      3.9      1.7      0.4,Versicolor
      Sepal L. Sepal W. Petal L. Petal W.
[1,]      7.0      3.2      4.7      1.4
[2,]      6.4      3.2      4.5      1.5
[3,]      6.9      3.1      4.9      1.5
[4,]      5.5      2.3      4.0      1.3
[5,]      6.5      2.8      4.6      1.5
[6,]      5.7      2.8      4.5      1.3,Virginica
      Sepal L. Sepal W. Petal L. Petal W.
[1,]      6.3      3.3      6.0      2.5
[2,]      5.8      2.7      5.1      1.9
[3,]      7.1      3.0      5.9      2.1
[4,]      6.3      2.9      5.6      1.8
[5,]      6.5      3.0      5.8      2.2
[6,]      7.6      3.0      6.6      2.1

解决方法

这可以通过迭代最后一个维度的顺序来实现，因为默认情况下lapply会遍历所有项目：

lapply(1:dim(arr)[3],function(i) cov(arr[,i]))

[[1]]
             Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length   0.12424898 0.099216327  0.016355102 0.010330612
Sepal.Width    0.09921633 0.143689796  0.011697959 0.009297959
Petal.Length   0.01635510 0.011697959  0.030159184 0.006069388
Petal.Width    0.01033061 0.009297959  0.006069388 0.011106122

[[2]]
             Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length   0.26643265  0.08518367   0.18289796  0.05577959
Sepal.Width    0.08518367  0.09846939   0.08265306  0.04120408
Petal.Length   0.18289796  0.08265306   0.22081633  0.07310204
Petal.Width    0.05577959  0.04120408   0.07310204  0.03910612

[[3]]
             Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length   0.40434286  0.09376327   0.30328980  0.04909388
Sepal.Width    0.09376327  0.10400408   0.07137959  0.04762857
Petal.Length   0.30328980  0.07137959   0.30458776  0.04882449
Petal.Width    0.04909388  0.04762857   0.04882449  0.07543265

如果您希望输出为3维数组

sapply(1:dim(arr)[3],i]),simplify="array") -> covar,1

             Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length   0.12424898 0.099216327  0.016355102 0.010330612
Sepal.Width    0.09921633 0.143689796  0.011697959 0.009297959
Petal.Length   0.01635510 0.011697959  0.030159184 0.006069388
Petal.Width    0.01033061 0.009297959  0.006069388 0.011106122,2

             Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length   0.26643265  0.08518367   0.18289796  0.05577959
Sepal.Width    0.08518367  0.09846939   0.08265306  0.04120408
Petal.Length   0.18289796  0.08265306   0.22081633  0.07310204
Petal.Width    0.05577959  0.04120408   0.07310204  0.03910612,3

             Sepal.Length Sepal.Width Petal.Length Petal.Width
Sepal.Length   0.40434286  0.09376327   0.30328980  0.04909388
Sepal.Width    0.09376327  0.10400408   0.07137959  0.04762857
Petal.Length   0.30328980  0.07137959   0.30458776  0.04882449
Petal.Width    0.04909388  0.04762857   0.04882449  0.07543265
# if you want to add names
dimnames(covar)[3] <- dimnames(arr)[3]

或者按照@ G.Grothendieck的评论

array(apply(arr,3,var),dim(arr)[c(2,2,3)],dimnames(arr)[c(2,3)])

数据

simplify2array(by(iris[-5],iris$Species,as.matrix)) -> arr
applycovariance-matrixrr