A comparison of designs obtained by statistical and deterministic methods is being carried out. Points that are difficult to address in the statistical approaches are considered. A formulation of a regularized solution to experimental design is described in detail. The peculiarities of the optimal design for three types of regressions are revealed. The main factors that govern the estimation errors are determined.

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[1] Mikhail Romanovski, "Inverse Problems and Parameter Estimation", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/mbfx-g028. Accessed: May. 22, 2024.
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author = {Mikhail Romanovski },
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title = {Inverse Problems and Parameter Estimation},
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Mikhail Romanovski. (2019). Inverse Problems and Parameter Estimation. IEEE Dataport. http://dx.doi.org/10.21227/mbfx-g028
Mikhail Romanovski, 2019. Inverse Problems and Parameter Estimation. Available at: http://dx.doi.org/10.21227/mbfx-g028.
Mikhail Romanovski. (2019). "Inverse Problems and Parameter Estimation." Web.
1. Mikhail Romanovski. Inverse Problems and Parameter Estimation [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/mbfx-g028
Mikhail Romanovski. "Inverse Problems and Parameter Estimation." doi: 10.21227/mbfx-g028