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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 smoothed_state(self,data,beta):
 """ Creates the negative log marginal likelihood of the model Parameters data : np.array Data to be smoothed beta : np.array Contains untransformed starting values for latent variables Returns - Smoothed states """
         

        T, Z, R, Q, H = self._ss_matrices(beta)
        alpha, V = univariate_KFS(data,Z,H,T,Q,R,0.0)
        return alpha, V