artificial                package:wle                R Documentation

_H_a_w_k_i_n_s, _B_r_a_d_u, _K_a_s_s'_s _A_r_t_i_f_i_c_i_a_l _D_a_t_a

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

     This data set was generated by Hawkins, Bradu and Kass in the 1984
     for illustrating some of the merits of a robust technique. The
     data set consists of 75 observations in four dimensions (one
     response and three explanatory variables). The first 10
     observations are bad leverage points, and the next four points are
     good leverage points (i.e., their *x* are outlying, but the
     corresponding _y_ fit the model quite well).

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

     data(artificial)

_F_o_r_m_a_t:

     'artificial' is a data frame with 75 cases (rows) and 4 variables
     (columns) where the last column is the dependent variable,
     'y.artificial' and 'x.artificial' (as a matrix) are also
     available.

_S_o_u_r_c_e:

     Hawkins, D.M., Bradu, D., and Kass, G.V. (1984) Location of
     several outliers in multiple regression data using elemental sets.
     _Technometrics,_ *26*, 197-208.

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

     Rousseeuw, P.J., and Leroy, A.M. (1987) _Robust regression and
     outliers detection,_ Wiley.

