radiusMinimaxIC           package:ROptEst           R Documentation

_G_e_n_e_r_i_c _f_u_n_c_t_i_o_n _f_o_r _t_h_e _c_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _r_a_d_i_u_s _m_i_n_i_m_a_x _I_C

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

     Generic function for the computation of the radius minimax IC.

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

     radiusMinimaxIC(L2Fam, neighbor, risk, ...)

     ## S4 method for signature 'L2ParamFamily,
     ##   UncondNeighborhood, asGRisk':
     radiusMinimaxIC(L2Fam, neighbor, risk, 
             loRad, upRad, z.start = NULL, A.start = NULL, upper = 1e5, 
             maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE)

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

   L2Fam: L2-differentiable family of probability measures. 

neighbor: object of class '"Neighborhood"'. 

    risk: object of class '"RiskType"'. 

     ...: additional parameters. 

   loRad: the lower end point of the interval to be searched. 

   upRad: the upper end point of the interval to be searched. 

 z.start: initial value for the centering constant. 

 A.start: initial value for the standardizing matrix. 

   upper: upper bound for the optimal clipping bound. 

 maxiter: the maximum number of iterations 

     tol: the desired accuracy (convergence tolerance).

    warn: logical: print warnings. 

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

     The radius minimax IC is computed.

_M_e_t_h_o_d_s:

     _L_2_F_a_m = "_L_2_P_a_r_a_m_F_a_m_i_l_y", _n_e_i_g_h_b_o_r = "_U_n_c_o_n_d_N_e_i_g_h_b_o_r_h_o_o_d", _r_i_s_k = "_a_s_G_R_i_s_k": 
          computation of the radius minimax IC for an L2 differentiable
          parametric family. 

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

     Matthias Kohl Matthias.Kohl@stamats.de

_R_e_f_e_r_e_n_c_e_s:

     Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not
     Knowing the Radius. Submitted. Appeared as discussion paper Nr.
     81.  SFB 373 (Quantification and Simulation of Economic
     Processes), Humboldt University, Berlin; also available under
     <URL:
     www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf>

     Kohl, M. (2005) _Numerical Contributions to the Asymptotic Theory
     of Robustness_.  Bayreuth: Dissertation.

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

     'radiusMinimaxIC'

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

     N <- NormLocationFamily(mean=0, sd=1) 
     radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(), 
                     risk=asMSE(), loRad=0.1, upRad=0.5)

