discrimin                package:ade4                R Documentation

_L_i_n_e_a_r _D_i_s_c_r_i_m_i_n_a_n_t _A_n_a_l_y_s_i_s (_d_e_s_c_r_i_p_t_i_v_e _s_t_a_t_i_s_t_i_c)

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

     performs a linear discriminant analysis.

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

     discrimin(dudi, fac, scannf = TRUE, nf = 2)
     plot.discrimin (x, xax = 1, yax = 2, ...) 
     print.discrimin (x, ...) 

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

    dudi: a duality diagram, object of class 'dudi'

     fac: a factor defining the classes of discriminant analysis

  scannf: a logical value indicating whether the eigenvalues bar plot
          should be displayed

      nf: if scannf FALSE, an integer indicating the number of kept
          axes

       x: an object of class 'discrimin'

     xax: the column number of the x-axis

     yax: the column number of the y-axis

     ...: further arguments passed to or from other methods

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

     returns a list of class 'discrimin' containing : 

      nf: a numeric value indicating the number of kept axes

     eig: a numeric vector with all the eigenvalues

      fa: a matrix with the loadings: the canonical weights

      li: a data frame which gives the canonical scores

      va: a matrix which gives the cosines between the variables and
          the canonical scores

      cp: a matrix which gives the cosines between the components and
          the canonical scores

      gc: a data frame which gives the class scores

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

     Daniel Chessel chessel@biomserv.univ-lyon1.fr

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

     'lda' in package 'MASS'

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

     data(chazeb)
     dis1 <- discrimin(dudi.pca(chazeb$tab, scan = FALSE), chazeb$cla, 
         scan = FALSE)
     dis1
     plot(dis1)

     data(skulls)
     plot(discrimin(dudi.pca(skulls, scan = FALSE), gl(5,30), 
         scan = FALSE))

