Module « scipy.stats.mstats »

Fonction kendalltau - module scipy.stats.mstats

Signature de la fonction kendalltau

def kendalltau(x, y, use_ties=True, use_missing=False, method='auto') 

Description

kendalltau.__doc__

    Computes Kendall's rank correlation tau on two variables *x* and *y*.

    Parameters
    ----------
    x : sequence
        First data list (for example, time).
    y : sequence
        Second data list.
    use_ties : {True, False}, optional
        Whether ties correction should be performed.
    use_missing : {False, True}, optional
        Whether missing data should be allocated a rank of 0 (False) or the
        average rank (True)
    method: {'auto', 'asymptotic', 'exact'}, optional
        Defines which method is used to calculate the p-value [1]_.
        'asymptotic' uses a normal approximation valid for large samples.
        'exact' computes the exact p-value, but can only be used if no ties
        are present. As the sample size increases, the 'exact' computation
        time may grow and the result may lose some precision.
        'auto' is the default and selects the appropriate
        method based on a trade-off between speed and accuracy.

    Returns
    -------
    correlation : float
        Kendall tau
    pvalue : float
        Approximate 2-side p-value.

    References
    ----------
    .. [1] Maurice G. Kendall, "Rank Correlation Methods" (4th Edition),
           Charles Griffin & Co., 1970.