ineq                  package:ineq                  R Documentation

_I_n_e_q_u_a_l_i_t_y _M_e_a_s_u_r_e_s

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

     computes the inequality within a vector according to the specified
     inequality measure

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

     ineq(x, parameter = NULL, type = c("Gini", "RS", "Atkinson", "Theil", "Kolm", "var",
          "square.var", "entropy"))

     Gini(x)
     RS(x)
     Atkinson(x, parameter = 0.5)
     Theil(x, parameter = 0)
     Kolm(x, parameter = 1)
     var.coeff(x, square = FALSE)
     entropy(x, parameter = 0.5)

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

       x: a vector containing at least non-negative elements

parameter: parameter of the inequality measure (if set to 'NULL' the
          default parameter of the respective measure is used)

    type: character string giving the measure used to compute
          inequality. must be one of the strings in the default
          argument (the first character is sufficient). defaults to
          "Gini".

  square: logical. Argument of the function 'var.coeff', for details
          see below.

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

     'ineq' is just a wrapper for the inequality measures 'Gini', 'RS',
     'Atkinson', 'Theil', 'Kolm','var.coeff', 'entropy'. If parameter
     is set to 'NULL' the default from the respective function is used.

     'Gini' is the Gini coefficient, 'RS' is the the Ricci-Schutz
     coefficient (also called Pietras measure), 'Atkinson' gives
     Atkinsons measure and 'Kolm' computes Kolms measure.

     If the parameter in 'Theil' is 0 Theils entropy measure is
     computed, for every other value Theils second measure is
     computed.

     'ineq(x, type="var")' and 'var.coeff(x)' respectively compute the
     coefficient of variation, while 'ineq(x,type="square.var")' and
     'var.coeff(x, square=TRUE)' compute the squared coefficient of
     variation.

     'entropy' computes the generalized entropy, which is for parameter
     1 equal to Theils entropy coefficient and for parameter 0 equal
     to the second measure of Theil.

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

     the value of the inequality measure

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

     Achim Zeileis zeileis@ci.tuwien.ac.at

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

     F A Cowell: Measurement of Inequality, 2000, in A B Atkinson / F
     Bourguignon (Eds): Handbook of Income Distribution, Amsterdam,

     F A Cowell: Measuring Inequality, 1995 Prentice Hall/Harvester
     Wheatshef,

     Marshall / Olkin: Inequalities: Theory of Majorization and Its
     Applications, New York 1979 (Academic Press).

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

     'conc', 'pov'

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

     # generate vector (of incomes)
     x <- c(541, 1463, 2445, 3438, 4437, 5401, 6392, 8304, 11904, 22261)
     # compute Gini coefficient
     ineq(x)
     # compute Atkinson coefficient with parameter=0.5
     ineq(x, parameter=0.5, type="Atkinson")

