7.1. Optimal Design problem

We start this chapter with the description of the general optimal design problems and concepts.

7.1.1. General Model

Consider a vector of observations Y = {y1,...,yN} and assume it follows a general parametric model. The joint probability density function of Y depends on x and θ, where x is the independent, or design, variable and θ = (θ1,.....,θm) is the vector of unknown model parameters. The design variable x is chosen, or controlled, by researchers to obtain the best estimates of the unknown parameters.

This general model can be applied to a wide variety of problems arising in clinical and pre-clinical studies. The examples considered in this chapter are described below. Dose-Response Studies

Dose-response ...

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