printMIM                package:mimR                R Documentation

_F_u_n_c_t_i_o_n _f_o_r _p_r_i_n_t_i_n_g _d_a_t_a, _m_o_d_e_l_s, _p_a_r_a_m_e_t_e_r _e_s_t_i_m_a_t_e_s _e_t_c. _i_n _M_I_M

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

     Submits the command 'Print <letter>' where the possible letters
     can be looked up in the MIM online help or David Edwards, An
     Introduction to Graphical Modelling, Springer Verlag, 2002. The
     result is interpreted in a suitable way and returned to the user

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

     printMIM(arg = NULL, verbose=FALSE)

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

     arg: A letter or NULL. When NULL the model is returned. See
          'details' below.

 verbose: If TRUE noting is printed

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

     S: empirical counts, means and covariances

     T: empirical counts, linear parameters and precisions

     U: empirical counts, means and correlations

     V: empirical counts, linear parameters and partial correlations

     F: fitted counts, means and covariances

     G: fitted counts, linear parameters and precisions

     H: fitted counts, means and correlations

     I: fitted counts, linear parameters and partial correlations

     NULL (the default): the formula of the current model. In block
     mode, this is the current block-recursive model, otherwise, it is
     the current undirected model.

     M: the formula of the current undirected model.

     B: the formula of the current block-recursive model.

     W: The AIC and BIC of the current model.

     X: minus twice the log likelihood of the saturated (or maximum)
     model

     Y: minus twice the log likelihood of the current model

     Z: the deviance of the current model.

     C: the raw data (using value labels)

     D: the raw data (using levels)

     E: the raw data (showing missing values)

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

     What is returned depend on the arg, i.e. on the letter

_N_o_t_e:

     Before using mimR, make sure that the MIM program is runnning.

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

     Sren Hjsgaard, sorenh@agrsci.dk

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

     David Edwards, An Introduction to Graphical Modelling, Springer
     Verlag, 2002

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

     'mim.cmd'

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

     mim.cmd("fact a2 b2 c2; statread abc")
     mim.cmd("25 2 17 8 14 9 6 8 !") 
     mim.cmd("mod ab,ac,bc; fit")
     printMIM("f")
     printMIM("s")

