pcoscaled                package:ade4                R Documentation

_S_i_m_p_l_i_f_i_e_d _A_n_a_l_y_s_i_s _i_n _P_r_i_n_c_i_p_a_l _C_o_o_r_d_i_n_a_t_e_s

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

     performs a simplified analysis in principal coordinates,  using an
     object of class 'dist'.

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

     pcoscaled(distmat, tol = 1e-07)

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

 distmat: an object of class 'dist'

     tol: a tolerance threshold, an eigenvalue is considered as
          positive if it is larger than '-tol*lambda1' where 'lambda1'
          is the largest eigenvalue

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

     returns a data frame containing the Euclidean representation of
     the distance matrix with a total inertia equal to 1

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

     Daniel Chessel chessel@biomserv.univ-lyon1.fr

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

     Gower, J. C. (1966) Some distance properties of latent root and
     vector methods used in multivariate analysis. _Biometrika_, *53*,
     325-338.

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

     library(mva)
         a <- 1 / sqrt(3) - 0.2
         w <- matrix(c(0,0.8,0.8,a,0.8,0,0.8,a,
             0.8,0.8,,0,a,a,a,a,0),4,4)
         w <- as.dist(w)
         w <- cailliez(w)
         w
         pcoscaled(w)
         dist(pcoscaled(w)) # w
         dist(pcoscaled(2 * w)) # the same
         sum(pcoscaled(w)^2) # unity

