utils.stats.partial_correlation_test

utils.stats.partial_correlation_test(x, y, z, method='pearson')

The partial correlation coefficient between x and y given z. x and y should be arrays (vectors) of the same length, and z should be a data frame (matrix).

Parameters

Name	Type	Description	Default
x	array - like	The first variable as a 1-dimensional array or list.	required
y	array - like	The second variable as a 1-dimensional array or list.	required
z	pandas.DataFrame	A data frame containing other conditional variables.	required
method	str	Correlation method, one of ‘pearson’, ‘kendall’, or ‘spearman’.	'pearson'

Returns

Name	Type	Description
dict	dict	A dictionary with the partial correlation estimate, p-value, statistic, sample size (n), number of given parameters (gp), and method used.

References

1. Kim, S. ppcor: An R package for a fast calculation to semi-partial correlation coefficients. Commun Stat Appl Methods 22, 6 (Nov 2015), 665–674.

Examples

>>> from spotpython.utils.stats import pairwise_partial_correlation
>>> import pandas as pd
>>> x = [1, 2, 3]
>>> y = [4, 5, 6]
>>> z = pd.DataFrame({'C': [7, 8, 9]})
>>> pairwise_partial_correlation(x, y, z)
{'estimate': -1.0, 'p_value': 0.0, 'statistic': -inf, 'n': 3, 'gp': 1, 'method': 'pearson'}