mif-class                package:pomp                R Documentation

_T_h_e "_m_i_f" _c_l_a_s_s

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

     The 'mif' class holds a fitted model and is created by a call to
     'mif'. See 'mif' for usage.

_O_b_j_e_c_t_s _f_r_o_m _t_h_e _C_l_a_s_s:

     Objects can be created by calls to the 'mif' method on an 'pomp'
     object. Such a call uses the MIF algorithm to fit the model
     parameters.

_S_l_o_t_s:

     A 'mif' object is derived from a 'pomp' object and therefore has
     all the slots of such an object. See 'pomp-class' for details. A
     full description of slots in a 'mif' object follows.

     _i_v_p_s A character vector containing the names of initial-value
          parameters (IVPs). These are parameters which are to be
          estimated using fixed-lag smoothing.

     _p_a_r_s A character vector containing the names of parameters to be
          estimated using MIF.

     _N_m_i_f Number of MIF iterations that have been completed.

     _p_a_r_t_i_c_l_e_s A function of prototype 'particles(Np,center,sd,...)'
          that draws particles from a distribution centered on 'center'
          and with width proportional to 'sd'. This function can be
          optionally specified by the user.

     _a_l_g._p_a_r_s A named list of algorithm parameters. This consists of
          'Np', the number of particles to use in filtering; 
          'var.factor', the scaling coefficient relating the width of
          the initial particle distribution to 'rw.sd'; 'ic.lag', the
          fixed lag used in the estimation of initial-value parameters
          (IVPs); and 'cooling.factor', the exponential cooling factor,
          where '0<cooling.factor<1'.

     _r_a_n_d_o_m._w_a_l_k._s_d A named vector containing the random-walk variance
          to be used for ordinary parameters.

     _p_r_e_d._m_e_a_n Matrix of prediction means. See 'pfilter'.

     _p_r_e_d._v_a_r Matrix of prediction variances. See 'pfilter'.

     _f_i_l_t_e_r._m_e_a_n Matrix of filtering means. See 'pfilter'.

     _e_f_f._s_a_m_p_l_e._s_i_z_e A vector containing the effective number of 
          particles at each time point. See 'pfilter'.

     _c_o_n_d._l_o_g_l_i_k A vector containing the conditional log likelihoods at
          each time point. See 'pfilter'.

     _c_o_n_v._r_e_c The convergence record: a matrix containing a record of
          the parameter values, log likelihoods, and other pertinent
          information, with one row for each MIF iteration.

     _l_o_g_l_i_k A numeric value containing the value of the log likelihood,
          as evaluated for the random-parameter model. Note that this
          will not be equal to the log likelihood for the
          fixed-parameter model.

     _d_a_t_a, _t_i_m_e_s, _t_0, _r_p_r_o_c_e_s_s, _d_p_r_o_c_e_s_s, _d_m_e_a_s_u_r_e, _r_m_e_a_s_u_r_e, _s_k_e_l_e_t_o_n._t_y_p_e, _s_k_e_l_e_t_o_n, _i_n_i_t_i_a_l_i_z_e_r, _s_t_a_t_e_s, _p_a_r_a_m_s, _s_t_a_t_e_n_a_m_e_s, _p_a_r_a_m_n_a_m_e_s, _c_o_v_a_r_n_a_m_e_s, _t_c_o_v_a_r, _c_o_v_a_r, _P_A_C_K_A_G_E, _u_s_e_r_d_a_t_a 
          Inherited from the 'pomp' class.


_E_x_t_e_n_d_s:

     Class 'pomp', directly. See 'pomp-class'.

_M_e_t_h_o_d_s:

     See 'mif', mif-methods, particles-mif, pfilter-mif.

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

     Aaron A. King kingaa at umich dot edu

_R_e_f_e_r_e_n_c_e_s:

     E. L. Ionides, C. Bret\'o, & A. A. King, Inference for nonlinear
     dynamical systems, Proc. Natl. Acad. Sci. U.S.A., 103:18438-18443,
     2006.

     A. A. King, E. L. Ionides, M. Pascual, and M. J. Bouma, Inapparent
     infections and cholera dynamics, Nature, 454:877-880, 2008.

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

     'mif', mif-methods, 'pomp', pomp-class

