ordtest                package:labdsv                R Documentation

_O_r_d_i_n_a_t_i_o_n _D_i_s_t_r_i_b_u_t_i_o_n _T_e_s_t

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

     Testing the distribution of points in an ordination

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

     ordtest(ord, var, dim=c(1:ncol(ord$points)), index = 'euclidean',
        nitr = 1000)

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

     ord: an object of class 'pca', 'pco', or 'nmds'

     var: a logical or factor vector used to organize the calculation
          of within-set distances

     dim: the number of dimensions to use in the calculation

   index: the distance metric for the calculation of within-set
          distances.   Currently only euclidean is accepted

    nitr: the number of iteration to perform to establish p-values

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

     Calculates the sum of within-set pair-wise distances and compares
     to 'nitr' permutations of the same distribution to calculate the
     probability of observing clusters as tight as observed or tighter.
      The p-value is calculated by running nitr-1 permutations and
     counting the number of cases where the sum of pair-wise distances
     is as small as smaller than observed.   That count is increased by
     one and divided by nitr to estimate p.

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

     Produces a list with components: 

     obs: the observed sum of within-set distances

       p: the probability of obtaining a value that small

    reps: the sum of within-set pairwise distances for all permutations

_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>

_S_e_e _A_l_s_o:

     'anosim'

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

     data(bryceveg)
     data(brycesite)
     dis.bc <- dsvdis(bryceveg,'bray/curtis')
     pco.bc <- pco(dis.bc)
     plot(pco.bc)
     demo <- ordtest(pco.bc,brycesite$quad)
     demo$p

