agnes.object             package:cluster             R Documentation

_A_g_g_l_o_m_e_r_a_t_i_v_e _N_e_s_t_i_n_g (_A_G_N_E_S) _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     The objects of class '"agnes"' represent an agglomerative
     hierarchical clustering of a dataset.

_V_a_l_u_e:

     A legitimate 'agnes' object is a list with the following
     components: 

   order: a vector giving a permutation of the original observations to
          allow for plotting, in the sense that the branches of a
          clustering tree will not cross.

order.lab: a vector similar to 'order', but containing observation
          labels instead of observation numbers. This component is only
          available if the original observations were labelled. 

  height: a vector with the distances between merging clusters at the
          successive stages. 

      ac: the agglomerative coefficient, measuring the clustering
          structure of the dataset.

          For each observation i, denote by m(i) its dissimilarity to
          the first cluster it is merged with, divided by the
          dissimilarity of the merger in the final step of the
          algorithm.  The 'ac' is the average of all 1 - m(i). It can
          also be seen as the average width (or the percentage filled)
          of the banner plot.  Because 'ac' grows with the number of
          observations, this measure should not be used to compare
          datasets of very different sizes. 

   merge: an (n-1) by 2 matrix, where n is the number of observations. 
          Row i of 'merge' describes the merging of clusters at step i
          of the clustering.  If a number j in the row is negative,
          then the single observation |j| is merged at this stage.  If
          j is positive, then the merger is with the cluster formed at
          stage j of the algorithm. 

    diss: an object of class '"dissimilarity"' (see
          'dissimilarity.object'), representing the total dissimilarity
          matrix of the dataset. 

    data: a matrix containing the original or standardized
          measurements, depending on the 'stand' option of the function
          'agnes'. If a dissimilarity matrix was given as input
          structure, then this component is not available. 

_G_E_N_E_R_A_T_I_O_N:

     This class of objects is returned from 'agnes'.

_M_E_T_H_O_D_S:

     The '"agnes"' class has methods for the following generic
     functions: 'print', 'summary', 'plot'.

_I_N_H_E_R_I_T_A_N_C_E:

     The class '"agnes"' inherits from '"twins"'. Therefore, the
     generic functions 'pltree' and 'as.hclust' are available for
     'agnes' objects. After applying 'as.hclust()', all _its_ methods
     are available, of course.

_S_e_e _A_l_s_o:

     'agnes', 'diana', 'as.hclust', 'hclust', 'plot.agnes',
     'twins.object'.

