def lpr_kurtosis(frame, lpcorder=10):
    """
    frame: windowed signal
    return kurtosis of linear prediction residual from input signal
    """
    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)