ContaminationSize          package:distrEx          R Documentation

_G_e_n_e_r_i_c _F_u_n_c_t_i_o_n _f_o_r _t_h_e _C_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _C_o_n_v_e_x _C_o_n_t_a_m_i_n_a_t_i_o_n 
(_P_s_e_u_d_o-)_D_i_s_t_a_n_c_e _o_f _T_w_o _D_i_s_t_r_i_b_u_t_i_o_n_s

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

     Generic function for the computation of convex contamination
     (pseudo-)distance  of two probability distributions P and Q. That
     is, the  minimal size 0 <= epsilon <= 1 is computed such that 
     there exists some probability distribution R with

                    Q = (1 - epsilon)P + epsilon R

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

     ContaminationSize(e1, e2)

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

      e1: object of class '"Distribution"' 

      e2: object of class '"Distribution"' 

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

     Computes the distance from 'e1' to 'e2' respectively P to Q. This
     is not really a distance as it is not symmetric!

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

     A list containing the following components: 

      e1: object of class '"Distribution"'; ideal distribution  

      e2: object of class '"Distribution"'; 'contaminated' distribution 

size.of.contamination: size of contamination 

_M_e_t_h_o_d_s:

     _e_1 = "_A_b_s_c_o_n_t_D_i_s_t_r_i_b_u_t_i_o_n", _e_2 = "_A_b_s_c_o_n_t_D_i_s_t_r_i_b_u_t_i_o_n": convex
          contamination (pseudo-)distance of two absolutely continuous
          univariate distributions.

     _e_1 = "_D_i_s_c_r_e_t_e_D_i_s_t_r_i_b_u_t_i_o_n", _e_2 = "_D_i_s_c_r_e_t_e_D_i_s_t_r_i_b_u_t_i_o_n": convex
          contamination (pseudo-)distance of two discrete  univariate
          distributions.

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

     Matthias Kohl Matthias.Kohl@stamats.de

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

     Huber, P.J. (1981) _Robust Statistics_. New York: Wiley.

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

     'KolmogorovDist', 'TotalVarDist',  'HellingerDist',
     'Distribution-class'

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

     ContaminationSize(Norm(), Norm(mean=0.1))
     ContaminationSize(Pois(), Pois(1.5))

