conditional_independence.gauss_invariance_test

conditional_independence.gauss_invariance_test(suffstat, context, i: int, cond_set: Optional[Union[List[int], int]] = None, alpha: float = 0.05, zero_mean=False, same_coeffs=False)

Test the null hypothesis that two Gaussian distributions are equal.

Parameters

• suffstat –

  dictionary containing:

  • obs – number of samples

  • G – Gram matrix

  • contexts

• context – which context to test.

• i – position of marginal distribution.

• cond_set – positions of conditioning set in correlation matrix.

• alpha – Significance level.

• zero_mean – If True, assume that the regression residual has zero mean.

• same_coeffs – If True, assume that the regression coefficients have not changed.

Returns

dictionary containing ttest_stat, ftest_stat, f_pvalue, t_pvalue, and reject.

Return type

dict