class_docstr: Base class that all volatility updaters must inherit from.
  
  Notes
  -----
  See the implementation available for information on modifying ``__init__``
  to capture model-specific parameters and how ``initialize_update`` is
  used to precompute values that change in each likelihood but not
  each iteration of the recursion.
  
  When writing a volatility updater, it is recommended to follow the
  examples in recursions.pyx which use Cython to produce a C-callable
  update function that can then be used to improve performance. The
  subclasses of this abstract metaclass are all pure Python and
  model estimation performance is poor since loops are written
  in Python.
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code: def __init__(self) -> None:
      pass
  
imports: from __future__ import annotations
  from arch.compat.numba import jit
  from abc import ABCMeta, abstractmethod
  from typing import cast
  import numpy
  from scipy.special import gammaln
  from arch.typing import Float64Array, Int32Array
  from arch.utility.array import AbstractDocStringInheritor
label_desc: Use image node_id 1 to create a new VolatilityUpdater object  with example: obj = VolatilityUpdater()