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))

