fwdmvEigenvectorPlot         package:Rfwdmv         R Documentation

_P_l_o_t _t_h_e _C_o_m_p_o_n_e_n_t_s _o_f _a_n _E_i_g_e_n_v_e_c_t_o_r _i_n _a_n _f_w_d_m_v _O_b_j_e_c_t

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

     Plots (for each group in the 'fwdmv' object) the components of the
     specified eigenvector of the covariance matrix against the subset
     size.

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

     fwdmvEigenvectorPlot(x, which.vector = 1, correlation = FALSE, psfrag.labels = FALSE)

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

       x: an 'fwdmv' object.

which.vector: an integer value used to select the eigenvector whose
          components are to be plotted.

correlation: a logical value.  If 'TRUE' then the eigenvectors of the
          correlation matrix are plotted.

psfrag.labels: a logical value.  If 'TRUE' then the x, y, and main
          labels are set to "xlab", "ylab", and "main" for replacement
          via the psfrag utility.

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

     an empty list is returned invisibly.

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

     Kjell Konis

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

     Atkinson, A. C., Riani, M. and Cerioli, A. (2004) Exploring
     Multivariate Data with the Forward Search. Springer-Verlag New
     York.

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

     'fwdmv.object', 'fwdmv'

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

     data(fondi.dat)
     fondi.1 <- fwdmv(fondi.dat)
     fwdmvEigenvectorPlot(fondi.1)

