AUC                   package:ROC                   R Documentation

_f_u_n_c_t_i_o_n_a_l_s _o_f _R_O_C _c_u_r_v_e

_D_e_s_c_r_i_p_t_i_o_n:

     various functionals of ROC (Receiver Operating Characteristic)
     curves

_U_s_a_g_e:

     AUC(rocobj)
     AUCi(rocobj)
     pAUC(rocobj,t0)
     pAUCi(rocobj,t0)

_A_r_g_u_m_e_n_t_s:

  rocobj: element of class rocc

      t0: FPR point at which TPR is evaluated  or limit in (0,1) to
          integrate to

_D_e_t_a_i_l_s:

     AUC, pAUC, AUCi and pAUCi compute the Area Under the Curve.

     AUC and pAUC employ the trapezoidal rule.  AUCi and pAUCi use
     integrate().

     AUC and AUCi compute the area under the curve from 0 to 1 on the
     x-axis (i.e., the 1 - specificity axis).

     pAUC and pAUCi compute the are under the curve from 0 to argument
     t0 on the x-axis (i.e., the 1 - specificity axis).

     Elements of class rocc can be created by rocdemo.sca() or other
     constructors you might make using the code of rocdemo.sca() as a
     template.

_V_a_l_u_e:

_N_o_t_e:

_A_u_t_h_o_r(_s):

     Vince Carey (stvjc@channing.harvard.edu)

_R_e_f_e_r_e_n_c_e_s:

     Rosner, B., 2000, _Fundamentals of Biostatistics, 5th Ed._, pp.
     63-65

     Duda, R. O., Hart, P. E., Stork, D. G., 2001 _Pattern
     Classification, 2nd Ed._, p. 49

_S_e_e _A_l_s_o:

     rocdemo.sca

_E_x_a_m_p_l_e_s:

     set.seed(123)
     R1 <- rocdemo.sca( rbinom(40,1,.3), rnorm(40), dxrule.sca,
        caseLabel="new case", markerLabel="demo Marker" )
     print(AUC(R1))
     print(pAUC(R1,.3))
     print(pAUCi(R1,.3))
     print(ROC(R1,.3))