

flou(multiv)                                 R Documentation

_F_u_z_z_y _C_o_d_i_n_g _(_3_-_W_a_y_)

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

     Simple fuzzy, or piecewise linear, coding of a vector:
     each value in the vector is replaced by a 1 (if it is
     above or equal to the 67th quantile), by a 0 (if it is
     below or equal to the 33rd quantile), and by a linearly
     interpolated value between 0 and 1 (if it lies between
     the 33rd and 67th quantiles).

_U_s_a_g_e_:

     flou(a)

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

       a: real-valued vector, with no missing values.

_V_a_l_u_e_:

     matrix of `length(a)' rows, and two columns.  The first
     column contains the fuzzily coded values of `a', and
     the second column contains their complements.  Hence
     each row of this returned matrix necessarily sums to 1.

_B_A_C_K_G_R_O_U_N_D_:

     This form of coding is suitable for a subsequent corre-
     spondence analysis.  When all variable have been
     fuzzily (or logically) coded, the row masses (propor-
     tional to the row sums) are identical.

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

     J.-P. Benzecri Correspondence Analysis Handbook Marcel
     Dekker, Basel, 1992.

     F.J. Gallego, Codage flou en analyse des correspon-
     dances, Les Cahiers de l'Analyse des Donnees vol. VII,
     413-430, 1982

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

     `logique', `ca', `supplr', `supplc'.

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

     # Fuzzy coding of input variables, `a', `b', `c':
     a.fuzz <- flou(a)
     b.fuzz <- flou(b)
     c.fuzz <- flou(c)
     newdata <- cbind(a.fuzz, b.fuzz, c.fuzz)
     ca.newdata <- ca(newdata)

