chaospy.Kurt

chaospy.Kurt(poly, dist=None, fisher=True, **kws)

The forth order statistical moment Kurtosis.

Element by element 4rd order statistics of a distribution or polynomial.

Args:

poly (numpoly.ndpoly, Distribution):

Input to take kurtosis on.

dist (Distribution):

Defines the space the skewness is taken on. It is ignored if poly is a distribution.

fisher (bool):

If True, Fisher’s definition is used (Normal -> 0.0). If False, Pearson’s definition is used (normal -> 3.0)

Returns:

(numpy.ndarray):

Element for element variance along poly, where skewness.shape==poly.shape.

Examples:

>>> dist = chaospy.J(chaospy.Gamma(1, 1), chaospy.Normal(0, 2))
>>> chaospy.Kurt(dist).round(4)
array([6., 0.])
>>> chaospy.Kurt(dist, fisher=False).round(4)
array([9., 3.])
>>> q0, q1 = chaospy.variable(2)
>>> poly = chaospy.polynomial([1, q0, q1, 10*q0*q1-1])
>>> chaospy.Kurt(poly, dist).round(4)
array([nan,  6.,  0., 15.])
>>> chaospy.Kurt(4., dist)
array(nan)