alibi_detect.utils.statstest

Functions

fdr

fdr(p_val: numpy.ndarray, q_val: float) -> Tuple[int, Union[float, numpy.ndarray]]

Checks the significance of univariate tests on each variable between 2 samples of

multivariate data via the False Discovery Rate (FDR) correction of the p-values.

Name	Type	Default	Description
p_val	numpy.ndarray		p-values for each univariate test.
q_val	float		Acceptable q-value threshold.

Returns

• Type: Tuple[int, Union[float, numpy.ndarray]]

permutation_test

permutation_test(x: numpy.ndarray, y: numpy.ndarray, metric: Callable, n_permutations: int = 100, kwargs) -> Tuple[float, float, numpy.ndarray]

Apply a permutation test to samples x and y.

Name	Type	Default	Description
x	numpy.ndarray		Batch of instances of shape [Nx, features].
y	numpy.ndarray		Batch of instances of shape [Ny, features].
metric	Callable		Distance metric used for the test. Defaults to Maximum Mean Discrepancy.
n_permutations	int	100	Number of permutations used in the test.
kwargs			Kwargs for the metric. For the default this includes for instance the kernel used.

Returns

• Type: Tuple[float, float, numpy.ndarray]