code: def add_model_from_params(self, name, fit_filters, predict_filters,
                                model_expression, ytransform=None):
          
          logger.debug(
              'adding model {} to group {}'.format(name, self.name))
          model = RegressionModel(
              fit_filters, predict_filters, model_expression, ytransform, name)
          self.models[name] = model
docs: Add a model by passing arguments through to `RegressionModel`.
  
          Parameters
          ----------
          name : any
              Must match a groupby segment name.
          fit_filters : list of str
              Filters applied before fitting the model.
          predict_filters : list of str
              Filters applied before calculating new data points.
          model_expression : str
              A patsy model expression that can be used with statsmodels.
              Should contain both the left- and right-hand sides.
          ytransform : callable, optional
              A function to call on the array of predicted output.
              For example, if the model relation is predicting the log
              of price, you might pass ``ytransform=np.exp`` so that
              the results reflect actual price.
  
              By default no transformation is applied.