Cov                  package:rrcov                  R Documentation

_C_l_a_s_s_i_c_a_l _E_s_t_i_m_a_t_e_s _o_f _M_u_l_t_i_v_a_r_i_a_t_e _L_o_c_a_t_i_o_n _a_n_d _S_c_a_t_t_e_r

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

     Computes the classical estimates of multivariate location and
     scatter.  Returns an S4 class 'Cov' with the estimated 'center', 
     'cov', Mahalanobis distances and weights based on these distances.
      The class 'Cov' is used as a base class for the classes
     representing  the different robust estimators.

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

         Cov(x, unbiased=TRUE)

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

       x: a matrix or data frame. As usual, rows are observations and
          columns are variables. 

unbiased: whether to return the unbiased estimate of  the covariance
          matrix. Default is  'unbiased = TRUE'

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

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

     An object of class '"Cov"'.

_N_o_t_e:

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

     Valentin Todorov valentin.todorov@chello.at

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

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

     'Cov-class'

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

     data(hbk)
     hbk.x <- data.matrix(hbk[, 1:3])
     cv <- Cov(hbk.x)
     cv
     summary(cv)
     plot(cv)

