sphpca                  package:psy                  R Documentation

_S_p_h_e_r_i_c_a_l _R_e_p_r_e_s_e_n_t_a_t_i_o_n _o_f _a _C_o_r_r_e_l_a_t_i_o_n _M_a_t_r_i_x

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

     Graphical representation of a correlation matrix, similar to
     principal component analysis (PCA) but the mapping is on a sphere.
     The information is close to a 3d PCA, the picture is however
     easier to interpret since the variables are in fact on a 2d map.

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

     sphpca(datafile, h=0, v=0, f=0, cx=0.75, nbsphere=2, back=FALSE)

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

datafile: name of datafile

       h: rotation of the sphere on a horizontal plane (in degres)

       v: rotation of the sphere on a vertical plane (in degres)

       f: rotation of the sphere on a frontal plane (in degres)

      cx: size of the lettering (0.75 by default, 1 for bigger letters,
          0.5 for smaller)

nbsphere: two by default: front and back

    back: "FALSE" by default: the back sphere is not seen through

_D_e_t_a_i_l_s:

     The sphere may be rotated to help in visualising most of variables
     on a same side (front for example). By default, the back of the
     sphere (right plot) is not seen showing through. Computations are
     based on a principal components approximation (see reference for
     details).

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

     A plot

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

     Bruno Falissard

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

     Falissard B, A spherical representation of a correlation matrix,
     Journal of Classification (1996), 13:2, 267-280.

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

     data(sleep)
     sphpca(sleep[,c(2:5,7:11)])
     ##spherical representation of ecological and constitutional correlates in mammals

