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Module « scipy.stats.mstats »

Fonction trimmed_std - module scipy.stats.mstats

Signature de la fonction trimmed_std

def trimmed_std(a, limits=(0.1, 0.1), inclusive=(1, 1), relative=True, axis=None, ddof=0) 

Description

help(scipy.stats.mstats.trimmed_std)

Returns the trimmed standard deviation of the data along the given axis.


    Parameters
    ----------
    a : sequence
        Input array
    limits : {None, tuple}, optional
        If `relative` is False, tuple (lower limit, upper limit) in absolute values.
        Values of the input array lower (greater) than the lower (upper) limit are
        masked.

        If `relative` is True, tuple (lower percentage, upper percentage) to cut
        on each side of the  array, with respect to the number of unmasked data.

        Noting n the number of unmasked data before trimming, the (n*limits[0])th
        smallest data and the (n*limits[1])th largest data are masked, and the
        total number of unmasked data after trimming is n*(1.-sum(limits))
        In each case, the value of one limit can be set to None to indicate an
        open interval.

        If limits is None, no trimming is performed
    inclusive : {(bool, bool) tuple}, optional
        If `relative` is False, tuple indicating whether values exactly equal
        to the absolute limits are allowed.
        If `relative` is True, tuple indicating whether the number of data
        being masked on each side should be rounded (True) or truncated
        (False).
    relative : bool, optional
        Whether to consider the limits as absolute values (False) or proportions
        to cut (True).
    axis : int, optional
        Axis along which to trim.

ddof : {0,integer}, optional
    Means Delta Degrees of Freedom. The denominator used during computations
    is (n-ddof). DDOF=0 corresponds to a biased estimate, DDOF=1 to an un-
    biased estimate of the variance.

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