FIM_uncomp_inhibition

vector of <code>S</code> component of design points. <code>S</code> is the substrate concentration.

vector of <code>I</code> component of design points. <code>I</code> is the inhibitor concentration.

vector of corresponding weights for each design point.
Its length must be equal to the length of <code>I</code> and <code>S</code>, and <code>sum(w)</code> should be 1.

vector of model parameters $(V, Km, Kiu)$.

param


The mean velocity of the reaction rate is
 $$\eta =  \frac{VS}{(K_m + S(1 + \frac{I}{K_{iu}}))}.$$
 Here, $S$ is the substrate concentration, $I$ is the inhibitor concentration,
  $V$ is the maximum velocity of the enzyme, $Kiu$ is the dissociation constants and
   $Km$ is the Michaelis-Menten constant. Any design point is of the form $(S, I)$.


Finding locally D-optimal, minimax D-optimal, standardized maximin D-optimal, optim-on-the-average and multiple objective optimal designs for nonlinear models. Different Fisher information matrices can also be set by user. There are also  useful functions for verifying the optimality of the designs with respect to different criteria by equivalence theorem. ICA is a meta-heuristic evolutionary algorithm inspired from the socio-political process of humans. See Masoudi et al. (2016) <doi:10.1016/j.csda.2016.06.014>.

FIM_uncomp_inhibition: Fisher information matrix for the uncompetitive inhibition Michaelis-Menten model.

Description

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