cmdscale                 package:mva                 R Documentation

_C_l_a_s_s_i_c_a_l (_M_e_t_r_i_c) _M_u_l_t_i_d_i_m_e_n_s_i_o_n_a_l _S_c_a_l_i_n_g

_D_e_s_c_r_i_p_t_i_o_n:

     Classical multidimensional scaling of a data matrix.

_U_s_a_g_e:

     cmdscale(d, k = 2, eig = FALSE)

_A_r_g_u_m_e_n_t_s:

       d: a distance structure such as that returned by `dist' or a
          full symmetric matrix containing the dissimilarities.

       k: the dimension of the space which the data are to be
          represented in.

     eig: indicates whether eigenvalues should be returned.

_D_e_t_a_i_l_s:

     Multidimensional scaling takes a set of dissimilarities and
     returns a set of points such that the distances between the points
     are approximately equal to the dissimilarities.

     The functions `isoMDS' and `sammon' in package `MASS' provide
     alternative ordination techniques.

_V_a_l_u_e:

     If `eig = FALSE', a matrix with `k' columns whose rows give the
     coordinates of the points chosen to represent the dissimilarities.

     Otherwise, a list containing the following components. 

  points: a matrix with `k' columns whose rows give the coordinates of
          the points chosen to represent the dissimilarities.

     eig: the eigenvalues computed during the scaling process.

_N_o_t_e:

     The S version of this function provides for computing an
     additional ``fiddle'' factor suggested by Torgerson.  R does not
     provide this option.

_R_e_f_e_r_e_n_c_e_s:

     Seber, G. A. F. (1984). Multivariate Analysis. New York: Wiley.

     Torgerson, W. S. (1958). Theory and Methods of Scaling. New York:
     Wiley.

_S_e_e _A_l_s_o:

     `dist'. Also `isoMDS' and `sammon' in package `MASS'.

_E_x_a_m_p_l_e_s:

     data(eurodist)
     loc <- cmdscale(eurodist)
     x <- loc[,1]
     y <- -loc[,2]
     plot(x, y, type="n", xlab="", ylab="")
     text(x, y, names(eurodist), cex=0.5)

