

supplc(multiv)                               R Documentation

_S_u_p_p_l_e_m_e_n_t_a_r_y _C_o_l_u_m_n_s _i_n _C_o_r_r_e_s_p_o_n_d_e_n_c_e _A_n_a_l_y_s_i_s

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

     Using the results of a correspondence analysis, project
     new columns into the factor space.

_U_s_a_g_e_:

     supplc(a, ca.res)

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

       a: data matrix to be projected.  Must have same num-
          ber of rows as matrix which was initially input to
          the correspondence analysis.

  ca.res: the output of a correspondence analysis.  The fol-
          lowing components of this object are used:
          `evals', `rproj' and `cproj'.

_V_a_l_u_e_:

     a matrix, projections of the columns of `a' on the cor-
     respondence analysis factors.

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

     See function `ca'.

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

     Correspondence analysis: `ca'.  Supplementary rows and
     columns: `supplr', `supplc'.  Initial data coding:
     `flou', `logique'.  Other functions producing objects
     of class "reddim": `pca', `sammon'.  Other related
     functions: `prcomp', `cancor', `cmdscale'.  Plotting
     tool: `plaxes'.

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

     cares <- ca(logarray)
     newproj <- supplc(newcols, cares)
     # plot of first and second factors, and of supplementary columns:
     plot(cares$cproj[,1], cares$cproj[,2],type="n")
     text(cares$cproj[,1], cares$cproj[,2])
     points(newproj[,1], newproj[,2])
     # Place additional axes through x=0 and y=0:
     plaxes(cares$cproj[,1], cares$cproj[,2])

