cov.trob package:MASS R Documentation _C_o_v_a_r_i_a_n_c_e _E_s_t_i_m_a_t_i_o_n _f_o_r _M_u_l_t_i_v_a_r_i_a_t_e _t _D_i_s_t_r_i_b_u_t_i_o_n _D_e_s_c_r_i_p_t_i_o_n: Estimates a covariance or correlation matrix assuming the data came from a multivariate t distribution: this provides some degree of robustness to outlier without giving a high breakdown point. _U_s_a_g_e: cov.trob(x, wt = rep(1, n), cor = FALSE, center = TRUE, nu = 5, maxit = 25, tol = 0.01) _A_r_g_u_m_e_n_t_s: x: data matrix. Missing values (NAs) are not allowed. wt: A vector of weights for each case: these are treated as if the case 'i' actually occurred 'wt[i]' times. cor: Flag to choose between returning the correlation ('cor = TRUE') or covariance ('cor = FALSE') matrix. center: a logical value or a numeric vector providing the location about which the covariance is to be taken. If 'center = FALSE', no centering is done; if 'center = TRUE' the MLE of the location vector is used. nu: 'degrees of freedom' for the multivariate t distribution. Must exceed 2 (so that the covariance matrix is finite). maxit: Maximum number of iterations in fitting. tol: Convergence tolerance for fitting. _V_a_l_u_e: A list with the following components cov: the fitted covariance matrix. center: the estimated or specified location vector. wt: the specified weights: only returned if the 'wt' argument was given. n.obs: the number of cases used in the fitting. cor: the fitted correlation matrix: only returned if 'cor = TRUE'. call: The matched call. iter: The number of iterations used. _R_e_f_e_r_e_n_c_e_s: J. T. Kent, D. E. Tyler and Y. Vardi (1994) A curious likelihood identity for the multivariate t-distribution. _Communications in Statistics-Simulation and Computation_ *23*, 441-453. Venables, W. N. and Ripley, B. D. (1999) _Modern Applied Statistics with S-PLUS._ Third Edition. Springer. _S_e_e _A_l_s_o: 'cov', 'cov.wt', 'cov.mve' _E_x_a_m_p_l_e_s: cov.trob(stackloss)