sinDAG                  package:SIN                  R Documentation

_S_I_N _f_o_r _a_c_y_c_l_i_c _d_i_r_e_c_t_e_d _g_r_a_p_h_s

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

     This function computes the matrix of simultaneous p-values for SIN
     model selection for acyclic directed graphs (DAGs).  SIN assumes
     that a total ordering of the variables is available (e.g., as a
     time-order).

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

     sinDAG(order,S,n)

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

   order: a list of pairwise different integers amongst 1,...,p where p
          is the number of variables.  This list specifies a total
          ordering of the variables by the convention that a list
          element is smaller than succeeding list elements.

       S: a covariance or correlation matrix.

       n: the sample size.

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

     A matrix of simultaneous p-values with 'NA' on the diagonal.

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

     Drton, M. & Perlman, M.D.  (2004)  Model Selection for Gaussian
     Concentration Graphs. _Biometrika_, to appear. 

      Drton, M. & Perlman, M.D.  (2004)  A SINful Approach to Gaussian
     Graphical Model Selection.  _Statistical Science_, to appear. 

      Drton, M. & Perlman, M.D.  (2003)  A SINful Approach to Model
     Selection for Gaussian Concentration Graphs. Department of
     Statistics, University of Washington, Technical Report 429.
      <URL:
     http://www.stat.washington.edu/www/research/reports/2003/tr429.pdf
     >

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

     'plotDAGpvalues'

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

     data(fowlbones)
     p <- dim(fowlbones$corr)[1]
     sinDAG(list(1:p),fowlbones$corr,fowlbones$n)
     holm(sinDAG(list(1:p),fowlbones$corr,fowlbones$n))
     sinDAG(list(3,2,1,4,5,6),fowlbones$corr,fowlbones$n)

