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On the computational methods in non-linear design of experiments
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Abstract(s)
In this paper the non-linear problem is discussed, for point and interval computational estimation. For the interval estimation an adjusted formulation is discussed due to Beale’s measure of non-linearity. The non-linear experimental design problem is regarded when the errors of observations are assumed i.i.d. and normally distributed as usually. The sequential approach is adopted. The average-per-observation information matrix is adopted to the developed theoretical approach. Different applications are discussed and we provide evidence that the sequential approach might be the panacea for solving a non-linear optimal experimental design problem.
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Keywords
Experimental design Optimal design Fisher’s information Autoregressive model Linear models Non-linear models Beale’s measure Optimization Fisher’s information Design measure
