profiler                 package:nls                 R Documentation

_C_o_n_s_t_r_u_c_t_o_r _f_o_r _P_r_o_f_i_l_e_r _O_b_j_e_c_t_s _f_o_r _N_o_n_l_i_n_e_a_r _M_o_d_e_l_s

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

     Create a profiler object for the model object `fitted'.

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

     profiler(fitted, ...)

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

  fitted: the original fitted model object.

     ...: Additional parameters. See documentation on individual
          methods.

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

     An object of class `"profiler"' which is a list with function
     elements 

getFittedPars(): the parameters in `fitted' 

setDefault(varying, params): this is used for changing the default
          settings for profiling. In absence of both parameters, the
          default is set to the original fitted parameters with all
          parameters varying. The arguments are

          `varying': a logical, integer or character vector giving
          parameters to be varied. `params': the default value at which
          profiling is to take place. 

getProfile(varying, params): this can be used in conjunction with
          `setDefault' without any arguments. Alternatively, the
          parameters to be varied and the values for fixed parameters
          can be specified using the arguments. The arguments are

          `varying': a logical vector giving parameters to be varied.
          This can be omitted if params is a named list or numeric
          vector.

          `params': values for parameters to be held fixed.

          It returns a list with elements

          `parameters': the parameter values for the profiled optimum.

          `fstat': a profile statistics. See individual methods for
          details.

          `varying': a logical vector indicating parameters which were
          varied. 

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

     Douglas M. Bates and Saikat DebRoy

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

     `profiler.nls', `profile'

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

     # see documentation on individual methods

