@classmethod
def probs(cls, x, y, rope=0, runs=1):
    """
        Compute and return probabilities

        Probabilities are not computed from a sample posterior but
        from cumulative Student distribution.

        Args:
            x (np.array): a vector of scores for the first model
            y (np.array): a vector of scores for the second model
            rope (float): the width of the region of practical equivalence (default: 0)
            runs (int): number of repetitions of cross validation (default: 1)

        Returns:
            `(p_left, p_rope, p_right)` if `rope > 0`;
            otherwise `(p_left, p_right)`.
        """
    return cls(x, y, rope, runs).probs()
