(self, name, fit_filters, predict_filters,
                              model_expression, ytransform=None)
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.
Add a model by passing arguments through to `RegressionModel`.
Add a model by passing arguments through to RegressionModel .
def add_model_from_params(self, name, fit_filters, predict_filters,
                              model_expression, ytransform=None):
        """
        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.

        """
        logger.debug(
            'adding model {} to group {}'.format(name, self.name))
        model = RegressionModel(
            fit_filters, predict_filters, model_expression, ytransform, name)
        self.models[name] = model
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