gompertz                 package:drc                 R Documentation

_M_e_a_n _f_u_n_c_t_i_o_n _f_o_r _t_h_e _G_o_m_p_e_r_t_z _d_o_s_e-_r_e_s_p_o_n_s_e _o_r _g_r_o_w_t_h _c_u_r_v_e

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

     This function provides a very general way of specifying the mean
     function of the decreasing or incresing  Gompertz dose-response or
     growth curve models.

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

       gompertz(fixed = c(NA, NA, NA, NA), names = c("b", "c", "d", "e"), 
       method = c("1", "2", "3", "4"), ssfct = NULL,
       fctName, fctText)

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

   fixed: numeric vector. Specifies which parameters are fixed and at
          what value they are fixed.  NAs for parameter that are not
          fixed.

   names: vector of character strings giving the names of the
          parameters (should not contain ":"). The order of the
          parameters is: b, c, d, e (see under 'Details' for the
          precise meaning of each parameter).

  method: character string indicating the self starter function to use.

   ssfct: a self starter function to be used.

 fctName: character string used internally by convenience functions
          (optional).

 fctText: character string used internally by convenience functions
          (optional).

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

     The Gompertz model is given by the mean function


                 f(x) = c + (d-c)(exp(-exp(b(x-e))))


     and it is a dose-response/growth curve on the entire real axis,
     that is it is not limited to non-negative values even though this
     is the range for most dose-response and growth data. One
     consequence is that the curve needs not reach the lower asymptote
     at dose 0.

     If 

                                 b<0

     the mean function is increasing and it is decreasing for 

                                 b>0

     . The decreasing Gompertz model is not a well-defined
     dose-response model and other dose-response models such as the
     Weibull models  should be used instead.

     Various re-parameterisations of the model are used in practice.

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

     The value returned is a list containing the non-linear function,
     the self starter function and the parameter names.

_N_o_t_e:

     The function is for use with the function 'drm', but typically the
     convenience functions 'G.2', 'G.3', 'G.3u', and 'G.4' should be
     used.

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

     Christian Ritz

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

     Seber, G. A. F. and Wild, C. J. (1989) _Nonlinear Regression_, New
     York: Wiley & Sons (p. 331).

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

     The Weibull model 'weibull2' is closely related to the Gompertz
     model.

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

     bg.m1 <- drm(weightInf~DAE, data = beetGrowth, fct = G.3())
     summary(bg.m1)
     plot(bg.m1)

