按组划分的相关矩阵 [英] Correlation matrix by group

问题描述

这是我的数据框

df <- structure(list(g1 = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L), .Label = c("A", "C"), class = "factor"), g2 = structure(c(1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L), .Label = c("a", "b"), class = "factor"), v1 = 1:10, v2 = c(5, 5, 6, 2, 4, 4, 2, 1, 9, 8), v3 = c(29, 10, 56, 93, 20, 14, 12, 87, 67, 37)), .Names = c("g1", "g2",  "v1", "v2", "v3"), row.names = c(NA, -10L), class = "data.frame")

   g1 g2 v1 v2 v3
1   A  a  1  5 29
2   A  a  2  5 10
3   A  a  3  6 56
4   A  b  4  2 93
5   A  b  5  4 20
6   C  a  6  4 14
7   C  a  7  2 12
8   C  b  8  1 87
9   C  b  9  9 67
10  C  b 10  8 37

我想为组G1和G2(在本例中为AA、AB、Ca、Cb)的每个组合创建v1、v2和v3的相关矩阵。所以我想使用Hmisc包并结合plyr

library(Hmisc)
library(plyr)

这是可行的(当然忽略组)：

rcorr(as.matrix(df[,3:5]), type="pearson")

但这不是：

cor.matrix <- dlply(df, .(g1,g2), rcorr(as.matrix(df[,3:5]), type="pearson"))
Error:attempt to apply non-function

我做错了什么？

推荐答案

如果每个组有4个以上的观察结果(因此我rbind将您的df添加到另外2个df中)：

df <- structure(list(g1 = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L), 
    .Label = c("A", "C"), class = "factor"), 
    g2 = structure(c(1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L), 
    .Label = c("a", "b"), class = "factor"), 
    v1 = 1:10, v2 = c(5, 5, 6, 2, 4, 4, 2, 1, 9, 8), 
    v3 = c(29, 10, 56, 93, 20, 14, 12, 87, 67, 37)), 
    .Names = c("g1", "g2",  "v1", "v2", "v3"), row.names = c(NA, -10L), 
    class = "data.frame")


df <- rbind(df, df, df)

library(Hmisc)
lapply(split(df, df[, 1:2]), function(x) {
    rcorr(as.matrix(x[,3:5]), type="pearson")
})

编辑有效：

dlply(df, .(g1,g2), function(x) rcorr(as.matrix(x[,3:5]), type="pearson"))

这篇关于按组划分的相关矩阵的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！