The mean of response variable is $$f(x, \bold{\theta}) = \theta_0 + \frac{\theta_1 x}{(x + \theta_2)}$$.
FIM_emax_3par(x, w, param)vector of design points.
vector of design weight. Its length must be equal to the length of x and sum(w) should be 1.
vector of model parameters \(\bold{\theta} = (\theta_0, \theta_1, \theta_2)\).
Fisher information matrix.
The model has an analytical solution for the locally D-optimal design. See Dette et al. (2010) for more details. The Fisher information matrix does not depend on \(\theta_0\).
Dette, H., Kiss, C., Bevanda, M., & Bretz, F. (2010). Optimal designs for the EMAX, log-linear and exponential models. Biometrika, 97(2), 513-518.
Other FIM: FIM_comp_inhibition,
FIM_exp_2par, FIM_exp_3par,
FIM_logisitic_1par,
FIM_logistic_4par,
FIM_logistic, FIM_loglin,
FIM_michaelis,
FIM_mixed_inhibition,
FIM_noncomp_inhibition,
FIM_power_logistic,
FIM_uncomp_inhibition