Fisher-z test
Perform an independence test using Fisher-z’s test 1. This test is optimal for linear-Gaussian data.
Usage
from causallearn.utils.cit import fisherz
p = fisherz(data, X, Y, condition_set, correlation_matrix)
Parameters
data: numpy.ndarray, shape (n_samples, n_features). Data, where n_samples is the number of samples and n_features is the number of features.
X, Y and condition_set: column indices of data.
correlation_matrix: correlation matrix; None means without the parameter of correlation matrix.
Returns
p: the p-value of the test.
- 1
Fisher, R. A. (1921). On the’probable error’of a coefficient of correlation deduced from a small sample. Metron, 1, 1-32.