

_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

     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_s_c_r_i_p_t_i_o_n:

     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 dis-
     similarities.

     The funtions `isomds' and `sammon' provide alternative
     ordination techniques.

_V_a_l_u_e:

     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: if requested,pthe 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 Togerson.
     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 Scal-
     ing.  New York: Wiley.

_S_e_e _A_l_s_o:

     `dist', `isomds', `sammon'.

_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)

