panel                 package:panel                 R Documentation

_A _f_u_n_c_t_i_o_n _t_o _c_o_m_p_u_t_e _t_h_e _m_a_x_i_m_u_m _l_i_k_e_l_i_h_o_o_d _e_s_t_i_m_a_t_e_s _o_f _t_h_e _t_r_a_n_s_i_t_i_o_n
_p_a_r_a_m_e_t_e_r_s _f_r_o_m _p_a_n_e_l _d_a_t_a.

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

     The algorithm is discussed in Kalbfleisch and Lawless (1985) and
     further in Gentleman (1994).

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

     panel(indata, qmatf, gamma, qderivf, npar, nstage, ncov, verbose = F,
             tol = 0.001)

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

  indata: indata is a list with one element for each individual. Each
          element of indata is a structure with 4 components.  time: a
          vector containing the inspection times stage: a vector
          containing the state of the individual at the  corresponding
          inspection time  cov: a vector containing the covariate
          values at the inspection times len: the number of inspections
          on  that individual 

    npar: npar is the number of parameters that are to be estimated 

  nstage: nstage is the number of stages/states in the model 

    ncov: ncov is the number of levels the covariate comes at 

   qmatf: qmatf is a function that accepts as input gamma (the
          parameters) and returns an array (ncov x nstage x nstage)
          with the ncov transition intensity matrices. 

   gamma: gamma is a vector (npar long) of estimates of the transition
          parameters. 

 qderivf: qderivf is a function that takes gamma as an argument and
          returns an array (npar x ncov x nstage x nstage) with the
          derivatives of the transition intensity matrices with respect
          to each of the parameters. 

 verbose: If verbose is set to TRUE then on each iteration the current
          estimate of theta and the current value of the score function
          are printed out. 

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

     panel returns a list with the parameter estimates, their standard
     errors and the log likelihood on convergence.

_S_i_d_e _E_f_f_e_c_t_s:

     There are no known side effects.

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

     Kalbfleisch J. D. and Lawless J. F. "The Analysis of Panel Data
     Under a Markov Assumption", JASA (1985), p. 863. Gentleman R.
     (1994). The Use of Covariate Information in Multi-state Markov
     Models. Technical Report 13, Department of Statistics, University
     of Auckland.

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

     eddcmp, dclike.panel

_E_x_a_m_p_l_e_s:

     #See the accompanying document "A Users Guide to panel" for
     #examples and code segments.

