Optimal Experimental Design Problem Research Articles

Optimal experiment design for autoregressive model with output power constraints

The output power constraint problem of optimal experiment design for an autoregressive model is considered. It is shown that besides the known minimum variance control law design, a D - optimal experiment consisting of sinusoidai input test signals without feedback can be obtained by solving a set of nonlinear equations. Two examples are also given to illustrate this design methodology.

Optimal experiment design for linear systems with input-output constraints

The problem of optimal experiment design for parameter estimation in linear dynamic systems is studied. Results relating to both constrained input and output variances are established. For the case of constrained input variance, it is shown that a D-optimal experiment exists in which the system input is generated externally provided the system and noise transfer functions have no common parameters. For the case of constrained output variance, it is shown that an experiment in which the system input is generated by a combination of a minimum variance control law together with an external set point perturbation is D-optimal for certain classes of systems. Other related results are also presented which illustrate the role of feedback in optimal experiment design.

The choice of estimators and experimental designs in a linear regression model according to a joint criterion of optimality

A decision theoretic model of the problem of optimal experimental design in a linear regression model is given which incldes both the choice of an estimator and the choice of an experimental design. Conditions are formulated, under which the complex problem is separable relative to minimax optimality in an estimation problem and a designing problem is investigated separately. With regard to minimax optimality and admisibility a justification as well as bounds of the usual classical approach to optimal experimental design are given. Moreover properties of robustness of designs against the loss are stated.

Analysis and design of certain scaling experiments.

IN certain psychological scaling techniques, direct pair comparison judgments of the differences between, or ratios of, magnitudes of attributes of objects (for example, volume or pitch of tones, heaviness of weights, painfulness of electric shocks) are elicited from a single subject1. We have investigated the statistical analysis of data thus obtained and the problem of optimal experimental design.