auROC                 package:limma                 R Documentation

_A_r_e_a _U_n_d_e_r _R_e_c_e_i_v_e_r _O_p_e_r_a_t_i_n_g _C_u_r_v_e

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

     Compute exact area under the ROC for empirical data.

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

     auROC(truth, stat)

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

   truth: numeric vector of 0 and 1 indicating whether the null or
          alternative respectively is true for each case. If 'stat' is
          missing then 'truth' is assuming to be already sorted in
          decreasing test statistic order.

    stat: numeric vector containing test statistics. Hypotheses are to
          be rejected if 'stat' exceeds a given threshold.

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

     This function computes the exact area under an empirical ROC
     curve. The number of true and false discoveries are determined by
     how well the true states represented by 'truth' match up with the
     observed statistics given by 'stat'.

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

     Numeric vector giving area under the curve, 1 being perfect and 0
     being the minimum, or 'NULL' if 'truth' has zero length.

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

     Gordon Smyth

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

     'AUC'

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

     auROC(c(1,1,0,0,0))
     truth <- rbinom(30,size=1,prob=0.2)
     stat <- rchisq(30,df=2)
     auROC(truth,stat)

