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Partial Correlation in Python
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""" | |
Partial Correlation in Python | |
Based on Fabian Pedregosa-Izquierdo's implementation at: | |
https://gist.github.com/fabianp/9396204419c7b638d38f | |
This version of the algorithm calculates the partial correlation coefficient controlling for Z. | |
I use row vectors here, for whatever reason. | |
""" | |
import numpy as np | |
def partial_corr(X,Z): | |
""" | |
Returns the partial correlation coefficients between elements of X controlling for the elements in Z. | |
""" | |
X = np.asarray(X).transpose() | |
Z = np.asarray(Z).transpose() | |
n = X.shape[1] | |
partial_corr = np.zeros((n,n), dtype=np.float) | |
for i in range(n): | |
partial_corr[i,i] = 1 | |
for j in range(i+1,n): | |
beta_i = np.linalg.lstsq(Z, X[:,j])[0] | |
beta_j = np.linalg.lstsq(Z, X[:,i])[0] | |
res_j = X[:,j] - Z.dot(beta_i) | |
res_i = X[:,i] - Z.dot(beta_j) | |
corr = np.corrcoef(res_i,res_j) | |
partial_corr[i,j] = corr.item(0,1) | |
partial_corr[j,i] = corr.item(0,1) | |
return partial_corr |
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