def skew(t):
"""
Computes the skewness of a :class:`Tensor`. Note: this function uses cross-approximation (:func:`tntorch.cross()`).
:param t: a :class:`Tensor`
:return: a scalar
"""
return tn.mean(((t - tn.mean(t)) / tn.std(t))**3)
def kurtosis(t, fisher=True):
"""
Computes the kurtosis of a :class:`Tensor`. Note: this function uses cross-approximation (:func:`tntorch.cross()`).
:param t: a :class:`Tensor`
:param fisher: if True (default) Fisher's definition is used, otherwise Pearson's (aka excess)
:return: a scalar
"""
return tn.mean(((t - tn.mean(t)) / tn.std(t))**4) - fisher * 3
def std(self, **kwargs):
"""
See :func:`metrics.std()`.
"""
return tn.std(self, **kwargs)
