如何计算R中的相关性 [英] How to calculate correlation In R

问题描述

我想计算R中的一个数据集x的子集的列之间的相关系数
我有40个模型的行，每8000个行中总共有200个仿真
我想计算之间的相关系数每次模拟的列（40行）

I wanted to calculate correlation coeficient between colunms of a subset of a data set x in R I have rows of 40 models each 200 simulations in total 8000 rows I wanted to calculate the corr coeficient between colums for each simulation (40 rows)

cor（x [c（3,5）]）计算得出全部8000行

我需要 cor（x [c（3,5）]），但仅当 X $ nsimul = 1 等等

cor(x[c(3,5)]) calculates from all 8000 rows
I need cor(x[c(3,5)]) but only when X$nsimul=1 and so on

在这方面，您会帮我吗？
San

would you help me in this regards San

推荐答案

我不确定您对 x [c（3,5）] 到底在做什么例如，您想要执行以下操作：您有一个数据框 X 这样：

I'm not sure what exactly you're doing with x[c(3,5)] but it looks like you want to do something like the following: You have a data-frame X like this:

set.seed(123)
X <- data.frame(nsimul = rep(1:2, each=5), a = sample(1:10), b = sample(1:10))

> X
   nsimul  a  b
1       1  1  6
2       1  8  2
3       1  9  1
4       1 10  4
5       1  3  9
6       2  4  8
7       2  6  5
8       2  7  7
9       2  2 10
10      2  5  3

您想用 nsimul 列拆分此数据帧，并计算<$每个组中的c $ c> a 和 b 。这是一个经典的 split-apply-combine 问题， plyr 软件包非常适合：

And you want to split this data-frame by the nsimul column, and calculate the correlation between a and b in each group. This is a classic split-apply-combine problem for which the plyr package is very well-suited:

require(plyr)
> ddply(X, .(nsimul), summarize, cor_a_b = cor(a,b))
  nsimul    cor_a_b
1      1 -0.7549232
2      2 -0.5964848

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