class_docstr: Tricube Kernel
  
  K(u) = 0.864197530864 * (1 - abs(x)**3)**3 between -1.0 and 1.0
class_docstr_tok: ["Tricube","Kernel","K","(","u",")","=","0.864197530864","*","(","1","-","abs","(","x",")","*","*","3",")","*","*","3","between","-1.0","and","1.0"]
code: def __init__(self, h=1.0):
      CustomKernel.__init__(
          self,
          shape=lambda x: 0.864197530864 * (1 - abs(x) ** 3) ** 3,
          h=h,
          domain=[-1.0, 1.0],
          norm=1.0,
      )
      self._L2Norm = 175.0 / 247.0
      self._kernel_var = 35.0 / 243.0
      self._order = 2
  
imports: from statsmodels.compat.python import lzip, lfilter
  import numpy
  import scipy.integrate
  from scipy.special import factorial
  from numpy import exp, multiply, square, divide, subtract, inf
label_desc: Use image node_id 1 to create a new Tricube object from inherited base classes: CustomKernel with example: obj = Tricube(h)