rnddist                package:labdsv                R Documentation

_R_a_n_d_o_m _D_i_s_t_a_n_c_e

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

     Calculates a random distance matrix for use in null  model
     analysis.

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

     rnddist(size, method='metric', sat = 1.0, upper=FALSE, diag=FALSE)

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

    size: the number of items to calculate the distances for

  method: the desired properties of the matrix.  Must be either
          'metric' or 'euclidean'

     sat: a saturation coefficient to set an upper limit less than 1.0
          that truncates maximum values to simulate a dissimilarity
          rather than a distance

   upper: logical: whether to print the upper triangle (default=FALSE)

    diag: logical: whether to print the diagonal (default=FALSE)

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

     Generates a matrix of size^2 uniform random numbers and passes the
     matrix to 'metrify' or  'euclidify' to ensure the metric or
     euclidean properties of the distances.  Values are normalized to a
     maximum of 1.0.

_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:

     'metrify', 'euclidify'

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

         x <- rnddist(100)
         pco.x <- pco(x)
         plot(pco.x)

