On the computational methods in non-linear design of experiments
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 ass...
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| Format: | bookPart |
| Language: | eng |
| Published: |
2021
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10400.2/10716 |
| Country: | Portugal |
| Oai: | oai:repositorioaberto.uab.pt:10400.2/10716 |
| Summary: | 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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