nls.control              package:stats              R Documentation

_C_o_n_t_r_o_l _t_h_e _I_t_e_r_a_t_i_o_n_s _i_n _n_l_s

_D_e_s_c_r_i_p_t_i_o_n:

     Allow the user to set some characteristics of the 'nls' nonlinear
     least squares algorithm.

_U_s_a_g_e:

     nls.control(maxiter=50, tol=1e-05, minFactor=1/1024)

_A_r_g_u_m_e_n_t_s:

 maxiter: A positive integer specifying the maximum number of
          iterations allowed.

     tol: A positive numeric value specifying the tolerance level for
          the relative offset convergence criterion.

minFactor: A positive numeric value specifying the minimum step-size
          factor allowed on any step in the iteration.  The increment
          is calculated with a Gauss-Newton algorithm and successively
          halved until the residual sum of squares has been decreased
          or until the step-size factor has been reduced below this
          limit.

_V_a_l_u_e:

     A 'list' with exactly three components: 

 maxiter: 

     tol: 

minFactor: 

     with meanings as explained under 'Arguments'.

_A_u_t_h_o_r(_s):

     Douglas Bates and Saikat DebRoy

_R_e_f_e_r_e_n_c_e_s:

     Bates and Watts (1988), _Nonlinear Regression Analysis and Its
     Applications_, Wiley.

_S_e_e _A_l_s_o:

     'nls'

_E_x_a_m_p_l_e_s:

     nls.control(minFactor = 1/2048)

