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:

     See 08.Tests for other functions for testing and processing
     p-values.

     See also 'AUC' in the 'ROC' package.

_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)