getstartvals             package:mvnmle             R Documentation

_O_b_t_a_i_n _s_t_a_r_t_i_n_g _v_a_l_u_e_s _f_o_r _m_a_x_i_m_u_m _l_i_k_e_l_i_h_o_o_d _e_s_t_i_m_a_t_i_o_n

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

     Calculates the starting values to be passed to `nlm' for
     minimization of the negative log-likelihood for multivariate
     normal data with missing values.  This function is private to
     `mlest'.

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

     getstartvals(x, eps=0.001)

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

       x: Multivariate data, potentially with missing values. 

     eps: All eigenvalues of the variance-covariance matrix less than
          `eps' times the smallest positive eigenvalue are set to `eps'
          times the smallest positive eigenvalue.

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

     Starting values for the mean vector are simply sample means. 
     Starting values for the variance-covariance matrix are derived
     from the sample variance-covariance matrix, after setting
     eigenvalues less than `eps' times the smallest positive eigenvalue
     equal to `eps' times the smallest positive eigenvalue to enforce
     positive definiteness.

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

     A numeric vector, containing the mean vector first, followed by
     the log of the diagonal elements of the inverse of the Cholesky
     factor of the adjusted sample variance-covariance matrix, and then
     the elements of the inverse of the Cholesky factor above the main
     diagonal.  These off-diagonal elements are ordered by column (left
     to right), and then by row within column (top to bottom).

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

     `mlest'

