code: def lpr_kurtosis(frame, lpcorder=10):
      
      c = lpc(frame, lpcorder)
      coef = c[1:][::-1] * -1
      residuals = []
      for i in xrange(frame.size - 10):
          residuals.append(frame[i + 10] - np.sum(frame[i:i + 10] * coef))
      residuals = np.array(residuals)
      return calc_kurtosis(residuals)
docs: frame: windowed signal
      return kurtosis of linear prediction residual from input signal