code: def __init__(self, endog, exog, M=None, missing="none", **kwargs):
      self._check_kwargs(kwargs)
      self.M = M if M is not None else norms.HuberT()
      super(base.LikelihoodModel, self).__init__(
          endog, exog, missing=missing, **kwargs
      )
      self._initialize()
      # things to remove_data
      self._data_attr.extend(["weights", "pinv_wexog"])
  
imports: import numpy
  import scipy.stats
  import statsmodels.base.model
  import statsmodels.base.wrapper
  import statsmodels.regression._tools
  import statsmodels.regression.linear_model
  import statsmodels.robust.norms
  import statsmodels.robust.scale
  from statsmodels.tools.decorators import cache_readonly
  from statsmodels.tools.sm_exceptions import ConvergenceWarning
label_desc: Use image node_id 1 to create a new RLM object from inherited base classes: base with example: obj = RLM(endog, exog, M, missing)