code: def __init__(
      self, smoother, alphas, gam, cost, endog, exog, cv_iterator
  ):
      self.cost = cost
      self.gam = gam
      self.smoother = smoother
      self.exog_linear = exog
      self.alphas = alphas
      self.cv_iterator = cv_iterator
      # TODO: super does not do anything with endog, exog, except get nobs
      # refactor to clean up what where `exog` and `exog_linear` is attached
      # exog is not used in super
      super().__init__(cv_iterator, endog, self.smoother.basis)
  
imports: from abc import ABCMeta, abstractmethod
  from statsmodels.compat.python import with_metaclass
  import itertools
  import numpy
  from statsmodels.gam.smooth_basis import GenericSmoothers, UnivariateGenericSmoother
label_desc: Use image node_id 1 to create a new MultivariateGAMCV object from inherited base classes: BaseCV with example: obj = MultivariateGAMCV(smoother, alphas, gam, cost, endog, exog, cv_iterator)