

cmdscale {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 muiltidimensional 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 dis-
     similarities.

     The functions `isoMDS' and `sammon' in package `MASS'
     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, 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)

