code: def calculate_parameters(self, independentTs, dependentTs):
          
          listX, listY = self.match_time_series(independentTs, dependentTs)
  
          if len(listX) == 0 or len(listY) == 0:
              raise ValueError("Lists need to have some equal dates or cannot be empty")
          if len(listX) != len(listY):
              raise ValueError("Each Timeseries need to have distinct dates")
  
          xValues = map(lambda item: item[1], listX)
          yValues = map(lambda item: item[1], listY)
  
          xMean = FusionMethods["mean"](xValues)
          yMean = FusionMethods["mean"](yValues)
  
          xDeviation = map(lambda item: (item - xMean), xValues)
          yDeviation = map(lambda item: (item - yMean), yValues)
  
          try:
              parameter1 = sum(x * y for x, y in zip(xDeviation, yDeviation)) / sum(x * x for x in xDeviation)
          except ZeroDivisionError:
              # error occures if xDeviation is always 0, which means that all x values are the same
              raise ValueError("Not enough distinct x values")
          parameter0 = yMean - (parameter1 * xMean)
  
          return (parameter0, parameter1)
docs: Calculate and return the parameters for the regression line
  
          Return the parameter for the line describing the relationship
          between the input variables.
  
          :param Timeseries independentTs: The Timeseries used for the
              independent variable (x-axis). The Timeseries must have
              at least 2 datapoints with different dates and values
          :param Timeseries dependentTs: The Timeseries used as the
              dependent variable (y-axis). The Timeseries must have
              at least 2 datapoints, which dates match with independentTs
  
          :return:    A tuple containing the y-axis intercept and the slope
                      used to execute the regression
          :rtype:     tuple
          :raise: Raises an :py:exc:`ValueError` if
                  - independentTs and dependentTs have not at least two matching dates
                  - independentTs has only one distinct value
                  - The dates in one or both Timeseries are not distinct.