yieldLoss                package:drc                R Documentation

_C_a_l_c_u_l_a_t_i_n_g _y_i_e_l_d _l_o_s_s _p_a_r_a_m_e_t_e_r_s

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

     Calculation of parameters in the re-parameterization of the
     Michaelis-Menten model that is commonly used to assess yield loss
     (the rectangular hyperbola model)

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

       yieldLoss(object, interval = c("none", "as"), level = 0.95, display = TRUE)

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

  object: object of class 'drc

interval: character string specifying the type of confidence intervals
          to be supplied. The default is "none".  Use "as" for
          asymptotically-based confidence intervals.

   level: numeric. The level for the confidence intervals. The default
          is 0.95.

 display: logical. If TRUE results are displayed. Otherwise they are
          not (useful in simulations).

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

     The rectangular hyperbola model is a reparameterization of the
     Michaelis-Menten in terms of parameters A and I


                        Y_L = frac{Id}{1+Id/A}


     where d denotes the weed density and Y_L the resulting yield loss.

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

     For each of the two parameters, a matrix with two or more columns,
     containing the estimates  and the corresponding estimated standard
     errors and possibly lower and upper confidence limits.

_N_o_t_e:

     This function is only for use with model fits based on
     Michaelis-Menten models.

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

     Christian Ritz

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

     Cousens, R. (1985). A simple model relating yield loss to weed
     density, _Ann. Appl. Biol._, *107*, 239-252.

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

     ## Fitting Michaelis-Menten model
     met.mm.m1 <- drm(gain~dose, product, data = methionine, fct = MM.3(), 
     pmodels = list(~1, ~factor(product), ~factor(product)))

     ## Yield loss parameters with standard errrors
     yieldLoss(met.mm.m1)

     ## Also showing confidence intervals
     yieldLoss(met.mm.m1, "as")

