ardi               package:SensoMineR               R Documentation

_A_u_t_o_m_a_t_i_c _R_e_s_e_a_r_c_h _o_f _D_I_v_e_r_g_e_n_c_e_s _b_e_t_w_e_e_n _s_c_o_r_e_s

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

     Spot the most singular or particular data with respect to all
     descriptors and to two qualitative variables and all their
     possible categories combinations.
      Computes the highest differences between all the  categories of
     the variables _product_, _panelist_ and all their possible
     combinations, with respect to a set of quantitative variables (the
     sensory descriptors).

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

     ardi(donnee, col.p, col.j, firstvar, lastvar = ncol(donnee), 
           nbval = 10, center = TRUE, scale = FALSE)

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

  donnee: a data frame made up of at least two qualitative variables 
          (_product_, _panelist_) and a set of quantitative variables
          (sensory descriptors)

   col.p: the position of the _product_ variable

   col.j: the position of the _panelist_ variable

firstvar: the position of the first sensory descriptor

 lastvar: the position of the last sensory descriptor (by default the
          last column of 'donnee')

   nbval: the number of highest divergences to be displayed

  center: by default, data are mean centered by panelist

   scale: by default, data are not scaled by panelist

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

     Step 1 For each quantitative variable, means by all the possible
     combinations (panelist,product) are computed. 
      Step 2 Then, data are mean centered and scaled to unit variance
     by descriptor and the divergence corresponds to the absolute value
     of the entries. 
      Step 3 Means on divergences are computed by products or by
     panelists and then sorted.

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

     A list containing the following elements: 

     tab: a data frame (descriptors are mean centered per panelist and
          scaled to unit variance)

panelist: a data frame, by default the 10 highest divergences between
          panelists according to the sensory descriptors

 product: a data frame, by default the 10 highest divergences between
          products according to the sensory descriptors

combination: a data frame, by default the 10 highest divergences
          between panelists and products according to the sensory
          descriptors

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

     Franois Husson, Sbastien L

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

     'decat'

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

     ## Not run: 
     data(chocolates)
     ardi(sensochoc, col.p = 4, col.j = 1, firstvar = 5)

     ## In the case where there's one particular variable of interest
     ardi(sensochoc, col.p = 4, col.j = 1, firstvar = 7, lastvar = 7)
     ## End(Not run)
       

