kfilter                package:sspir                R Documentation

_K_a_l_m_a_n _f_i_l_t_e_r _f_o_r _G_a_u_s_s_i_a_n _s_t_a_t_e _s_p_a_c_e _m_o_d_e_l

_D_e_s_c_r_i_p_t_i_o_n:

     From an SS object, runs the Kalman filter to produce the
     conditional means and variances of the state vectors given the
     current time point.

_U_s_a_g_e:

     kfilter(ss)

_A_r_g_u_m_e_n_t_s:

      ss: object of class 'SS'.

_D_e_t_a_i_l_s:

     The Kalman filter yields the distribution

                   (theta_t|y[,1:t]) ~ N(m_t, C_t)

     through the recursion for t=1,...,n,

                          a_t = G_t  m_{t-1}


                    R_t = G_t C_{t-1} G_t^T + W_t


                           f_t = F_t^T  a_t


                     Q_t = F_t^T  R_t  F_t + V_t


                           e_t = y_t - f_t


                       A_t = R_t  F_t  Q_t^{-1}


                         m_t = a_t + A_t  e_t


                     C_t = R_t - A_t  Q_t  A_t^T

     Also, the log-likelihood is calculated.

_V_a_l_u_e:

     An object of class 'SS' with the components 'm', 'C', and
     'likelihood' updated.

_A_u_t_h_o_r(_s):

     Claus Dethlefsen and Sren Lundbye-Christensen.

_S_e_e _A_l_s_o:

     'SS', 'smoother'

