PGM                  package:Icens                  R Documentation

_A_n _i_m_p_l_e_m_e_n_t_a_t_i_o_n _o_f _t_h_e _p_r_o_j_e_c_t_e_d _g_r_a_d_i_e_n_t _m_e_t_h_o_d_s _f_o_r _f_i_n_d_i_n_g
_t_h_e _N_P_M_L_E.

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

     An estimate of the NPMLE is obtained by using projected gradient
     methods. This method is a special case of the methods described in
     Wu (1978).

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

     PGM(A, pvec, maxiter = 500, tol=1e-07, told=2e-05, tolbis=1e-08,
         keepiter=FALSE)

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

       A: 'A' is either the m by n clique matrix or the n by 2 matrix
          containing the left and right end points for each event time. 

   pvec : An initial estimate of the probability vector. 

maxiter : The maximum number of iterations to take. 

     tol: The tolerance for decreases in likelihood. 

    told: 'told' does not seem to be used. 

  tolbis: The tolerance used in the bisection code. 

keepiter: A boolean indicating whether to return the number of
          iterations.  

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

     New directions are selected by the projected gradient method. The
     new optimal 'pvec' is obtained using the bisection algorithm,
     moving in the selected direction. Convergence requires both the
     L_1 distance for the improved 'pvec' and the change in likelihood
     to be below 'tol'.

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

     An object of class 'icsurv' containing the following components:  

     pf : The NPMLE of 'pvec'. 

  sigma : The cummulative sum of 'pvec'.

   lval : The value of the log likelihood at 'pvec'.

  clmat : The clique matrix. 

 method : The method used, currently only "MPGM" is possible. 

lastchange : The difference between 'pf' and the previous iterate. 

 numiter: The number of iterations carried out. 

     eps: The tolerances used. 

converge : A boolean indicating whether convergence occurred within
          'maxiter' iterations. 

   iter : If 'keepiter' is true then this is a matrix containing all
          iterations - useful for debugging.

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

     Alain Vandal and Robert Gentleman.

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

     _Some Algorithmic Aspects of the Theory of Optimal Designs_, C.-F.
     Wu, 1978, Annals.

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

     'VEM', 'ISDM', 'EMICM', 'PGM', 'EM'

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

         data(cosmesis)
         csub1 <- subset(cosmesis, subset=Trt==0, select=c(L,R))
         PGM(csub1)
         data(pruitt)
         PGM(pruitt)

