supplr                package:multiv                R Documentation

_S_u_p_p_l_e_m_e_n_t_a_r_y _R_o_w_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 rows
     into the factor space.

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

     supplr(a, ca.res)

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

       a: data matrix to be projected.  Must have same number of
          columns as matrix which was initially input to the
          correspondence analysis. 

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

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

     a list containing the matrix `proj',  projections of the rows of
     `a' on the correspondence 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'.

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

     data(USArrests)
     USArrests <- as.matrix(USArrests)
     corr <- ca(USArrests[1:25,])
     newproj <- supplc(USArrests[26:50,], corr)
     # plot of first and second factors, and of supplementary columns:
     plot(corr$cproj[,1], corr$cproj[,2],type="n")
     text(corr$cproj[,1], corr$cproj[,2])
     points(newproj$proj[,1], newproj$proj[,2], col=2) 

