xdiss                 package:mvpart                 R Documentation

_E_x_t_e_n_d_e_n_d _D_i_s_s_i_m_i_l_a_r_i_t_y _M_e_a_s_u_r_e_s

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

     The function computes extended dissimilarity indices which are for
     long gradients have better good rank-order relation with gradient
     separation and are thus efficient in community ordination with
     multidimensional scaling.

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

     xdiss(data, dcrit = 1, dauto = TRUE, dinf = 0.5, method = "man", 
         use.min = TRUE, eps = 1e-04, replace.neg = TRUE, big = 10000,
         sumry = TRUE, full = FALSE, sq = FALSE) 

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

    data: Data matrix

   dcrit: Dissimilarities < 'dcrit' are considered to have no species
          in common and are recalculated.

   dauto: Automatically select tuning parameters - recommended.

  method: Dissimilarity index 

 use.min: Minimum dissimilarity of pairs of distances used -
          recommended.

dinf, eps, replace.neg, big: Internal parameters - leave as is usually.

   sumry: Print summary of extended dissimilarities? 

    full: Return the square dissimilarity matrix. 

      sq: Square the dissimilarities - useful for distance-based
          partitionong. 

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

     The function knows the same dissimilarity indices as 'gdist'.

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

     Returns an object of class distance with attributes "Size" and
     "ok". "ok" is TRUE if rows are not disconnected (De'ath 1999).

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

     Glenn De'ath

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

     De'ath, G. (1999)  Extended dissimilarity: a method of robust
     estimation of ecological distances from high beta diversity data.
     _Plant Ecology_ 144(2):191-199.

     Faith, D.P, Minchin, P.R. and Belbin, L. (1987) Compositional
     dissimilarity as a robust measure of ecological distance.
     _Vegetatio_ 69, 57-68.

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

     data(spider)
     spider.dist <- xdiss(spider)

