dpcoa                  package:ade4                  R Documentation

_D_o_u_b_l_e _p_r_i_n_c_i_p_a_l _c_o_o_r_d_i_n_a_t_e _a_n_a_l_y_s_i_s

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

     Performs a double principal coordinate analysis

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

     dpcoa (df, dis = NULL, scannf = TRUE, nf = 2, full = FALSE, tol = 1e-07)
     plot.dpcoa (x, xax = 1, yax = 2, option = 1:4, csize = 2, ...)
     print.dpcoa (x, ...)

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

      df: a data frame with elements as rows, samples as columns and
          abundance or presence-absence as entries

     dis: an object of class 'dist' containing the distances between
          the elements.

  scannf: a logical value indicating whether the eigenvalues bar plot
          should be displayed

      nf: if scannf is FALSE, an integer indicating the number of kept
          axes

    full: a logical value indicating whether all non null eigenvalues
          should be kept

     tol: a tolerance threshold for null eigenvalues (a value less than
          tol times the first one is considered as null)

       x: an object of class 'dpcoa'

     xax: the column number for the x-axis

     yax: the column number for the y-axis

  option: the function 'plot.dpcoa' produces four graphs, 'option'
          allows us to choose only some of them

   csize: a size coefficient for symbols

     ...: '...' further arguments passed to or from other methods

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

     Returns a list of class 'dpcoa' containing: 

    call: call

      nf: a numeric value indicating the number of kept axes

      w1: a numeric vector containing the weights of the elements

      w2: a numeric vector containing the weights of the samples

     eig: a numeric vector with all the eigenvalues

  RaoDiv: a numeric vector containing diversities within samples

  RaoDis: an object of class 'dist' containing the dissimilarities
          between samples

RaoDecodiv: a data frame with the decomposition of the diversity

      l1: a data frame with the coordinates of the elements

      l2: a data frame with the coordinates of the samples

      c1: a data frame with the scores of the principal axes of the
          elements

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

     Daniel Chessel chessel@biomserv.univ-lyon1.fr 
      Sandrine Pavoine pavoine@biomserv.univ-lyon1.fr 
      Anne B Dufour dufour@biomserv.univ-lyon1.fr

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

     Pavoine, S., Dufour, A.B. and Chessel, D. (in press) From
     dissimilarities among species to dissimilarities among
     communities: a double principal coordinate analysis. _Journal of
     Theoretical Biology_.

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

     data(humDNAm)
     dpcoahum <- dpcoa(humDNAm$samples, sqrt(humDNAm$distances), scan = FALSE, nf = 2)
     dpcoahum
     plot(dpcoahum, csize = 1.5)
     ## Not run: 
     data(ecomor)
     ecomor.phylog <- taxo2phylog(ecomor$taxo)
     dpcoaeco <- dpcoa(ecomor$habitat, ecomor.phylog$Wdist, scan = FALSE, nf = 2)
     dpcoaeco
     plot(dpcoaeco, csize = 1.5)
     ## End(Not run)

