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Fonction moment - module scipy.stats

Signature de la fonction moment

def moment(a, moment=1, axis=0, nan_policy='propagate') 

Description

moment.__doc__

Calculate the nth moment about the mean for a sample.

    A moment is a specific quantitative measure of the shape of a set of
    points. It is often used to calculate coefficients of skewness and kurtosis
    due to its close relationship with them.

    Parameters
    ----------
    a : array_like
       Input array.
    moment : int or array_like of ints, optional
       Order of central moment that is returned. Default is 1.
    axis : int or None, optional
       Axis along which the central moment is computed. Default is 0.
       If None, compute over the whole array `a`.
    nan_policy : {'propagate', 'raise', 'omit'}, optional
        Defines how to handle when input contains nan.
        The following options are available (default is 'propagate'):

          * 'propagate': returns nan
          * 'raise': throws an error
          * 'omit': performs the calculations ignoring nan values

    Returns
    -------
    n-th central moment : ndarray or float
       The appropriate moment along the given axis or over all values if axis
       is None. The denominator for the moment calculation is the number of
       observations, no degrees of freedom correction is done.

    See Also
    --------
    kurtosis, skew, describe

    Notes
    -----
    The k-th central moment of a data sample is:

    .. math::

        m_k = \frac{1}{n} \sum_{i = 1}^n (x_i - \bar{x})^k

    Where n is the number of samples and x-bar is the mean. This function uses
    exponentiation by squares [1]_ for efficiency.

    References
    ----------
    .. [1] https://eli.thegreenplace.net/2009/03/21/efficient-integer-exponentiation-algorithms

    Examples
    --------
    >>> from scipy.stats import moment
    >>> moment([1, 2, 3, 4, 5], moment=1)
    0.0
    >>> moment([1, 2, 3, 4, 5], moment=2)
    2.0