plotBGpvalues              package:SIN              R Documentation

_P_l_o_t _s_i_m_u_l_t_a_n_e_o_u_s _p-_v_a_l_u_e_s _f_o_r _b_i_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 plots the simultaneous p-values for SIN model
     selection for bidirected graphs.

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

     plotBGpvalues(pvals, legend=T, legendpos=NULL)

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

   pvals: a matrix of p-values.

  legend: a Boolean.

legendpos: a numerical vector of length 2.

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

     A plot illustrating the simultaneous p-values.  If 'legend==TRUE',
     then a legend giving information on the variable labelling is
     drawn. Optionally, the position of the legend can be specified by
     'legendpos'.

_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:

     'sinBG'

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

     data(stressful)
     pvals <- holm(sinBG(stressful$corr,stressful$n))
     ## Not run: plotBGpvalues(pvals)
     ## Not run: plotBGpvalues(pvals, legend=F)
     ## Not run: plotBGpvalues(pvals, legendpos=c(5,0.5))
     ## Not run: plotBGpvalues(pvals, legend=T, legendpos=c(5,0.5))

