gap                   package:SAGx                   R Documentation

_G_A_P _s_t_a_t_i_s_t_i_c _c_l_u_s_t_e_r_i_n_g _f_i_g_u_r_e _o_f _m_e_r_i_t

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

     Calculates a goodness of clustering measure based on the average 
     dispersion compared to a reference distribution.

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

     gap(data = swiss,class = g, B = 500)

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

    data: The data matrix, with samples (observations) in rows and
          genes (variables)in columns

   class: a vector descibing the cluster memberships of the rows of
          data

       B: the number of bootstrap samples

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

     The GAP statistic

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

     Per Broberg

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

     Tishirani, R., Walther, G. and Hastie, T. (2000) Estimating the
     number of clusters in a dataset via the Gap statistic. _ Technical
     Report_ Stanford

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

     library("MASS")
     data(swiss)
     cl <- myclus(data = swiss, k = 3)
     gap(swiss,cl$cluster)

