Makes dynamic in-sample predictions with the estimated model

        Parameters
        ----------
        h : int (default : 5)
            How many steps would you like to forecast?

        Returns
        ----------
        - pd.DataFrame with predicted values

def predict_is(self,h=5):
        """ Makes dynamic in-sample predictions with the estimated model

        Parameters
        ----------
        h : int (default : 5)
            How many steps would you like to forecast?

        Returns
        ----------
        - pd.DataFrame with predicted values
        """     

        predictions = []

        for t in range(0,h):
            data1 = self.data_original.iloc[:-h+t,:]
            data2 = self.data_original.iloc[-h+t:,:] 
            x = NDynReg(formula=self.formula, data=data1, family=self.family)                                       
            x.fit(print_progress=False)
            if t == 0:
                predictions = x.predict(1,oos_data=data2)
            else:
                predictions = pd.concat([predictions,x.predict(1,oos_data=data2)])
        
        predictions.rename(columns={0:self.data_name}, inplace=True)
        predictions.index = self.index[-h:]

        return predictions