gompGrowth                package:drc                R Documentation

_G_o_m_p_e_r_t_z _g_r_o_w_t_h _m_o_d_e_l_s

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

     Gompertz growth model, with biologically meaningful parameters.
     Different parameterisations have been included for specific cases
     and needs.

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

     gompGrowth.1(fixed = c(NA, NA, NA), names = c("c", "m", "plateau"))
     gompGrowth.2(fixed = c(NA, NA, NA), names = c("c", "d", "plateau"))
     gompGrowth.3(fixed = c(NA, NA, NA), names = c("b", "c", "plateau"))

_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 default parameter
          names are: init, m, plateau.

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

     The Gompertz growth model is a Gompertz curve, that has been
     reparameterised to include some biologically  meaningful
     parameters. The mean function for gompGrowth.1() is:


      f(x) = f(x) = plateau * exp ( - (m/c) * exp ( - c *  x ) )


     The parameter plateau is the final plant weight, reached for x
     going to infinity the parameter c is relative growth rate at
     inflection point and the parameter m is the initial relative
     growth rate (when x=0). Thus the curve is monotonously increasing
     in x. The mean function for gompGrowth.2() is:


           f(x) = plateau * exp ( - exp ( c * ( d - x ) ))


     where the parameter c is the relative growth rate at inflection
     point and the parameter d is the abscissa of the  inflection
     point. The mean function for gompGrowth.3() is the classical
     Gompertz function:


           f(x) = plateau * exp ( - b * exp ( - c *  x ) )


     where b is proportional to the initial relative growth rate (m = b
     * c).

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

     A list of class 'drcMean', containing the mean function, the self
     starter function, the parameter names.

_N_o_t_e:

     Growth functions are generally fitted on log-transformed weight
     data, which equals to setting bc parameter to 0

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

     Andrea Onofri

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

     Roderick Hunt, 1982. Plant Growth Curves. Edward Arnold Publisher,
     Great Britain, 248 pp

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

     ## Fitting a Gompertz growth curve

     beet.model <- drm(weightInf ~ DAE, data  = beetGrowth, fct=gompGrowth.1())
     plot(beet.model, log = "")
     summary(beet.model)

