GLMM_longitDA             package:mixAK             R Documentation

_D_i_s_c_r_i_m_i_n_a_n_t _a_n_a_l_y_s_i_s _f_o_r _l_o_n_g_i_t_u_d_i_n_a_l _p_r_o_f_i_l_e_s _b_a_s_e_d _o_n _f_i_t_t_e_d _G_L_M_M'_s

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

     THIS FUNCTION IS BEING DEVELOPED AND ORDINARY USERS ARE NOT
     RECOMMENDED TO USE IT.

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

     GLMM_longitDA(mod, w.prior, y, id, time, x, z, xz.common=TRUE, info)

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

     mod: a list containing models fitted with the 'GLMM_MCMC'
          function. Each component of the list is the GLMM fitted in
          the training dataset of each cluster. 

 w.prior: a vector with prior cluster weights. The length of this
          argument must be the same as the length of argument 'mod'.
          Can also be given relatively, e.g., as 'c(1, 1)' which means
          that both prior weights are equal to 1/2. 

       y: vector, matrix or data frame (see argument 'y' of 'GLMM_MCMC'
          function) with responses of objects that are to be clustered. 

      id: vector which determines clustered observations (see also
          argument 'y' of 'GLMM_MCMC' function). 

    time: vector which gives indeces of observations within clusters.
          It appears (together with 'id') in the output as identifier
          of observations

       x: see 'xz.common' below.

       z: see 'xz.common' below.

xz.common: a logical value.

          If 'TRUE' then it is assumed that the X and Z matrices are
          the same for GLMM in each cluster. In that case, arguments
          'x' and 'z' have the same structure as arguments 'x' and 'z'
          of 'GLMM_MCMC' function.

          If 'FALSE' then X and Z matrices for the GLMM may differ
          across clusters. In that case, arguments 'x' and 'z' are both
          lists of length equal to the number of clusters and each
          component of lists 'x' and 'z' has the same structure as
          arguments 'x' and 'z' of 'GLMM_MCMC' function. 

    info: interval in which the function prints the progress of
          computation

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

     I HOPE TO WRITE A PAPER DESCRIBING ALL THE DETAILS.

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

     A list with the following components: 

   ident: ADD DESCRIPTION

    marg: ADD DESCRIPTION

    cond: ADD DESCRIPTION

   ranef: ADD DESCRIPTION

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

     Arno&#353t Kom&#225rek arnost.komarek[AT]mff.cuni.cz

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

     Kom&#225rek, A., Hansen, B. E., Kuiper, E. M. M., van Buuren, H.
     R., and Lesaffre, E. (2010). Discriminant analysis using a
     multivariate linear mixed model with a normal mixture in the
     random effects distribution. _Statistics in Medicine_. To appear.

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

     'GLMM_MCMC'.

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

     ### WILL BE ADDED.

