dqstep                 package:Bhat                 R Documentation

_s_t_e_p _s_i_z_e _g_e_n_e_r_a_t_o_r

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

     'dqstep' determines the smallest steps ds from s so that
     abs(f(s+ds)-f(s)) equals a pre-specified sensitivity

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

     dqstep(x, f, sens)

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

       x: a list with components 'label' (of mode character), 'est'
          (the parameter vector with the initial guess), 'low' (vector
          with lower bounds), and 'upp' (vector with upper bounds) 

       f: the function that is to be minimized over the parameter 
          vector defined by the list 'x' 

    sens: target sensitivity (i.e. the value of f(s+ds)-f(s)) 

_D_e_t_a_i_l_s:

     uses simple quadratic interpolation

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

     returns a vector with the desired step sizes

_N_o_t_e:

     This function is part of the Bhat exploration tool

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

     E. Georg Luebeck (FHCRC)

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

     'dfp', 'newton', 'logit.hessian'

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

       ## Rosenbrock Banana function
        fr <- function(x) {
              x1 <- x[1]
              x2 <- x[2]
              100 * (x2 - x1 * x1)^2 + (1 - x1)^2
         }
       ## define
        x <- list(label=c("a","b"),est=c(1,1),low=c(0,0),upp=c(100,100))
        dqstep(x,fr,sens=1)

