The optimal input design problem for the identification of linear compartmental models is studied. The optimality criterion consists in maximizing the achievable precision of parameter estimates. The rationale, theory, and computational methods for solving the problem for the scalar case are presented first. An application to a two-compartment model of glucose kinetics is then shown. The effect on parameter precision of the measurement error structure and of various design factors, such as an equienergy or equidose class of admissible inputs and the time interval for input and measurement, is discussed. The performance of standard classical inputs, e.g. an impulse or an infusion, is also evaluated.

Optimal input design for identification of compartmental models. Theory and application to a model of glucose kinetics.

COBELLI, CLAUDIO;
1985

Abstract

The optimal input design problem for the identification of linear compartmental models is studied. The optimality criterion consists in maximizing the achievable precision of parameter estimates. The rationale, theory, and computational methods for solving the problem for the scalar case are presented first. An application to a two-compartment model of glucose kinetics is then shown. The effect on parameter precision of the measurement error structure and of various design factors, such as an equienergy or equidose class of admissible inputs and the time interval for input and measurement, is discussed. The performance of standard classical inputs, e.g. an impulse or an infusion, is also evaluated.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2506785
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