deldupMclust              package:edci              R Documentation

_D_e_l_e_t_e _d_u_p_l_i_c_a_t_e _f_o_u_n_d _c_l_u_s_t_e_r_s

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

     Delete clusters differing only by rounding errors or having
     maximization value zero.

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

       deldupMclust(clust, prec=NULL, ncol=NULL, dz=TRUE)

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

   clust: numerical matrix, which columns contain the parameters of the
          clusters.

    prec: optional positive integer. Number of decimal places for
          rounding.

    ncol: Number of columns describing the clusters.

      dz: optional boolean. With 'dz=TRUE' clusters are deleted, for
          which the objective function has value 0.

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

     Since clusters found by 'oregMclust' or 'circMclust' often differ
     only by rounding errors, the function 'deldupMclust' can be used
     for rounding and deleting duplicates. If 'clust' has a column
     named 'count' their values are summed appropriate. Otherwise such
     a column is added.

     For parameter 'clust' the object returned from 'oregMclust' or
     'circMclust' can be used. Alternatively, an arbitrary matrix can
     be given, of which the first 'ncol' columns describe the clusters.
     The parameter 'prec' is the number of decimal places for rounding;
     the default is no rounding. With 'ncol' the number of columns,
     which describe the clusters, can be given. This is not needed, if
     'clust' is an object returned from 'oregMclust' or 'circMclust'.

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

     Return value is an object of the same type as 'clust'.

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

     Tim Garlipp, garlipp@mathematik.uni-oldenburg.de

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

     Mller, C.H., Garlipp, T. (2003) Simple consistent cluster methods
     based on redescending M-estimators with an application to edge
     identification in images, to appear in _JMVA_.

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

     'oregMclust', 'circMclust'

