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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def second_order_score(y, mean, scale, shape, skewness):
 """ GAS Laplace Update term potentially using second-order information - native Python function Parameters y : float datapoint for the time series mean : float location parameter for the Laplace distribution scale : float scale parameter for the Laplace distribution shape : float tail thickness parameter for the Laplace distribution skewness : float skewness parameter for the Laplace distribution Returns - Adjusted score of the Laplace family """

        return ((y-mean)/float(scale*np.abs(y-mean))) / (-(np.power(y-mean,2) - np.power(np.abs(mean-y),2))/(scale*np.power(np.abs(mean-y),3)))