ordcomp                package:labdsv                R Documentation

_O_r_d_i_n_a_t_i_o_n _t_o _D_i_s_s_i_m_i_l_a_r_i_t_y _C_o_m_p_a_r_i_s_o_n

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

     Plots the distribution of pair-wise distances of all points in an
     ordination to the distances in the dissimilarity or distance
     matrix the ordination was  calculated from.  Prints the
     correlation between the two on the graph.

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

     ordcomp(x,y,dim=2,xlab="Computed Distance",ylab="Ordination Distance",
                 title="",pch=1)

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

       x: an object of class 'dist'

       y: an ordination object from 'pca', 'pco', 'nmds', 'fso'

     dim: the number of dimensions in the ordination to use (default=2)

    xlab: the X axis label for the graph

    ylab: the Y axis label for the graph

   title: a title for the  plot

     pch: the symbol to plot

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

     a plot is created on the current graphics device

_N_o_t_e:

     Ordinations are low dimensional representations of
     multidimensional spaces.   This function attempts to portray how
     well the low dimensional solution approximates the  full
     dimensional space.

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

     David W. Roberts droberts@montana.edu <URL:
     http://ecology.msu.montana.edu/droberts>

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

     <URL: http://ecology.msu.montana.edu/labdsv/R>

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

     data(bryceveg) # produces a vegetation dataframe
     dis.bc <- dsvdis(bryceveg,'bray/curtis') # creates a Bray/Curtis dissimilarity matrix
     pco.bc <- pco(dis.bc,2) # produces a two-dimensional Principal Coordinates Ordination object
     ordcomp(pco.bc,dis.bc)

