simpvalueVec               package:SIN               R Documentation

_S_i_m_u_l_t_a_n_e_o_u_s _p-_v_a_l_u_e_s

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

     Simultaneous p-values are computed for a vector of correlations.
     Function only for internal use.

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

     simpvalueVec(corrs,n,p)

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

   corrs: a vector of correlations in (-1,1).

       n: the sample size.

       p: the number of variables.

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

     A vector of simultaneous p-values.

_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:

     'simpvalueMx'

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

     data(fowlbones)
     temp <- -solve(fowlbones$corr)
     diag(temp) <- abs(diag(temp))
     temp <- cov2cor(temp)
     p <- dim(temp)[1]
     round( simpvalueVec(temp[1,2:p],fowlbones$n,p), 2)

