loglik                package:mclust                R Documentation

_L_o_g_l_i_k_e_l_i_h_o_o_d _f_o_r _m_o_d_e_l-_b_a_s_e_d _h_i_e_r_a_r_c_h_i_c_a_l _c_l_u_s_t_e_r_i_n_g.

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

     Gives the loglikelihood for each stage of model-based hierarchical
     clustering.

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

     loglik(tree, data, Vinv)

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

    tree: an `"mhtree"' object. 

    data: the data used to produce the `"mhtree"' object. 

    Vinv: approximate recoprocal hypervolume of the region from which
          the data is drawn. The default (for those methods that need
          this quantity) is determined by the function `hypvol'. 

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

     the loglikelihood corresponding to the initial partition and to
     each stage of  merging in hierarchical clustering, together with
     the following attribute:

  nmerge: the number of clusters merged at each stage. 

_N_O_T_E_S:

     The value given is equal to the loglikelihood up to an additive
     constant.  For those models in which they arise, indeterminate
     terms are  assigned the value `-k*log(volume)', where `k' is the
     number of observations  associated with the term.  If you scaled
     your data before using `mhtree', be  sure to use the same scaling
     when supplying the data to `loglik'.

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

     `mhtree', `awe'

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

     data(iris)
     loglik(mhtree(iris[,1:4]),iris[,1:4])

