为什么corrcoef返回矩阵? [英] Why does corrcoef return a matrix?

问题描述

np.corrcoef返回一个矩阵对我来说似乎很奇怪.

It seems strange to me that np.corrcoef returns a matrix.

 correlation1 = corrcoef(Strategy1Returns,Strategy2Returns)

[[ 1.         -0.99598935]
 [-0.99598935  1.        ]]

有人知道为什么会这样吗，以及是否有可能仅返回经典意义上的一个值?

Does anyone know why this is the case and whether it is possible to return just one value in the classical sense?

推荐答案

它允许您计算> 2个数据集的相关系数，例如

It allows you to compute correlation coefficients of >2 data sets, e.g.

>>> from numpy import *
>>> a = array([1,2,3,4,6,7,8,9])
>>> b = array([2,4,6,8,10,12,13,15])
>>> c = array([-1,-2,-2,-3,-4,-6,-7,-8])
>>> corrcoef([a,b,c])
array([[ 1.        ,  0.99535001, -0.9805214 ],
       [ 0.99535001,  1.        , -0.97172394],
       [-0.9805214 , -0.97172394,  1.        ]])

在这里，我们可以立即获得a，b(0.995)，a，c(-0.981)和b，c(-0.972)的相关系数.两个数据集的情况只是N数据集类的一个特例.并且可能最好保持相同的返回类型.由于单一值"可以简单地通过

Here we can get the correlation coefficient of a,b (0.995), a,c (-0.981) and b,c (-0.972) at once. The two-data-set case is just a special case of N-data-set class. And probably it's better to keep the same return type. Since the "one value" can be obtained simply with

>>> corrcoef(a,b)[1,0]
0.99535001355530017

没有特殊理由创建特殊情况.

there's no big reason to create the special case.

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