EMICM                 package:Icens                 R Documentation

_C_o_m_p_u_t_e _t_h_e _N_P_M_L_E _f_o_r _c_e_n_s_o_r_e_d _d_a_t_a _u_s_i_n_g _t_h_e _E_M_I_C_M.

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

     An implementation of the hybrid EM ICM (Iterative convex minorant)
     estimator of the distribution function proposed by Wellner and
     Zahn (1997).

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

     EMICM(A, EMstep=TRUE, ICMstep=TRUE, keepiter=FALSE, tol=1e-07,
     maxiter=1000) 

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

       A: Either the m by n clique matrix or the n by 2 matrix
          containing the event time intervals. 

  EMstep: Boolean, indicating whether to take an EM step in the
          iteration. 

 ICMstep: Boolean, indicating whether to take an ICM step. 

keepiter: Boolean determining whether to keep the iteration states. 

     tol: The maximal L1 distance between successive estimates before
          stopping iteration. 

 maxiter: The maximal number of iterations to perform before stopping. 

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

     Lots, and they're complicated too!

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

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

     pf : The estimated probabilities.

  sigma : The NPMLE of the survival function on the maximal antichains. 

weights : The diagonal of the likelihood function's second derivative. 

lastchange : A vector of differences between the last two iterations. 

numiter : The total number of iterations performed.

   iter : Is only present if 'keepiter' is true; states of sigma 
          during the iteration.

 intmap : The real representation associated with the probabilities
          reported in 'pf'.

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

     Alain Vandal and Robert Gentleman

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

     _A hybrid algorithm for computation of the nonparametric maximum
     likelihood estimator from censored data_, J. A. Wellner and Y.
     Zhan, 1997, JASA.

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

     'EM','VEM', 'PGM'

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

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

