logistic                 package:drc                 R Documentation

_T_h_e _l_o_g_i_s_t_i_c _m_o_d_e_l

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

     The general asymmetric five-parameter logistic model for
     describing dose-response relationships.

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

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

       L.3(fixed = c(NA, NA, NA), names = c("b", "d", "e"), ...)
       L.4(fixed = c(NA, NA, NA, NA), names = c("b", "c", "d", "e"), ...)
       L.5(fixed = c(NA, NA, NA, NA, NA), names = c("b", "c", "d", "e", "f"), ...)  

_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: a vector of character strings giving the names of the
          parameters (should not contain ":").  The order of the
          parameters is: b, c, d, e, f (see under 'Details').

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

   ssfct: a self starter function to be used.

 fctName: optional character string used internally by convenience
          functions.

 fctText: optional character string used internally by convenience
          functions.

     ...: Additional arguments (see 'llogistic').

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

     The default arguments yields the five-parameter logistic mean
     function given by the expression


              f(x) = c + frac{d-c}{(1+exp(b(x - e)))^f}


     The model is different from the log-logistic models 'llogistic'
     and 'llogistic2' where the term 

                                log(x)

     is used instead of 

                                  x

     .

     The model is sometimes referred to as the Boltzmann model.

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

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

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

     Christian Ritz

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

     ## Fitting the four-parameter logistic model
     ryegrass.m1 <- drm(rootl ~ conc, data = ryegrass, fct = L.4())
     summary(ryegrass.m1)

     ## Fitting an asymmetric logistic model
     ##  requires installing the package 'NISTnls'
     # Ratkowsky3.m1 <- drm(y~x, data = Ratkowsky3, 
     # fct = L.5(fixed = c(NA, 0, NA, NA, NA)))
     # plot(Ratkowsky3.m1)
     # summary(Ratkowsky3.m1)  
     ## okay agreement with NIST values
     ##  for the two parameters that are the same

