lepidium                 package:drc                 R Documentation

_D_o_s_e-_r_e_s_p_o_n_s_e _p_r_o_f_i_l_e _o_f _d_e_g_r_a_d_a_t_i_o_n _o_f _a_g_r_o_c_h_e_m_i_c_a_l _u_s_i_n_g _l_e_p_i_d_i_u_m

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

     Estimation of the degradation profile of an agrochemical based on
     soil samples at depth 0-10cm from a calibration experiment.

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

     data(lepidium)

_F_o_r_m_a_t:

     A data frame with 42 observations on the following 2 variables.

     '_c_o_n_c' a numeric vector of concentrations (g/ha)

     '_w_e_i_g_h_t' a numeric vector of plant weight (g) after 3 weeks'
          growth

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

     It is an experiment with seven concentrations and six replicates
     per concentration. _Lepidium_ is rather robust as it only responds
     to high concentrations.

_S_o_u_r_c_e:

     Racine-Poon, A. (1988) A Bayesian Approach to Nonlinear
     Calibration Problems,  _J. Am. Statist. Ass._, *83*, 650-656.

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

     lepidium.m1 <- drm(weight~conc, data=lepidium, fct = LL.4())

     modelFit(lepidium.m1)

     plot(lepidium.m1, type = "all", log = "")

