parcor                  package:ggm                  R Documentation

_P_a_r_t_i_a_l _c_o_r_r_e_l_a_t_i_o_n_s

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

     Finds the matrix of the partial correlations between pairs of
     variables given the rest.

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

     parcor(S)

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

       S: a symmetric positive definite matrix, representing a
          covariance matrix.

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

     The algorithm computes - sigma^{rs}/(sigma^{rr} sigma^{ss})^{1/2}
     where the sigma^{rs} are concentrations, i.e. elements of the
     inverse covariance matrix.

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

     A symmetric matrix with ones along the diagonal and in position
     (r,s) the partial correlation between variables r and s given all
     the remaining variables.

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

     Giovanni M. Marchetti

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

     Cox, D. R. & Wermuth, N. (1996). _Multivariate dependencies_.
     London: Chapman & Hall.

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

     'var', 'cor', 'correlations'

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

     ### Partial correlations for the mathematics marks data
     data(marks)
     S <- var(marks)
     parcor(S)

