class_docstr: Test class for observation and state intercepts (which usually do not
  get tested in other models).
code: def __init__(self, endog, **kwargs):
      k_states = 3
      k_posdef = 3
      super().__init__(
          endog, k_states=k_states, k_posdef=k_posdef, **kwargs
      )
      self["design"] = np.eye(3)
      self["obs_cov"] = np.eye(3)
      self["transition"] = np.eye(3)
      self["selection"] = np.eye(3)
      self["state_cov"] = np.eye(3)
      self.initialize_approximate_diffuse()
  
imports: import numpy
  import pandas
  import os
  import pytest
  from statsmodels.tsa.statespace import mlemodel, sarimax
  from statsmodels import datasets
  from numpy.testing import assert_equal, assert_allclose, assert_raises
label_desc: Use image node_id 1 to create a new Intercepts object from inherited base classes: mlemodel with example: obj = Intercepts(endog)