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calculate Pearson correlation along with the confidence interval using scipy and numpy
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import numpy as np | |
from scipy import stats | |
def pearsonr_ci(x,y,alpha=0.05): | |
''' calculate Pearson correlation along with the confidence interval using scipy and numpy | |
Parameters | |
---------- | |
x, y : iterable object such as a list or np.array | |
Input for correlation calculation | |
alpha : float | |
Significance level. 0.05 by default | |
Returns | |
------- | |
r : float | |
Pearson's correlation coefficient | |
pval : float | |
The corresponding p value | |
lo, hi : float | |
The lower and upper bound of confidence intervals | |
''' | |
r, p = stats.pearsonr(x,y) | |
r_z = np.arctanh(r) | |
se = 1/np.sqrt(x.size-3) | |
z = stats.norm.ppf(1-alpha/2) | |
lo_z, hi_z = r_z-z*se, r_z+z*se | |
lo, hi = np.tanh((lo_z, hi_z)) | |
return r, p, lo, hi |
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