Optimal Experimental Design
An Optimal Experimental Design is a experimental design that ...
- See: Active Learning Algorithm, Objective Function, Estimation Theory, Statistical Model, Bias of an Estimator, Minimum-Variance Unbiased Estimator, Replication (Statistics), Parametric Model, Efficiency (Statistics).
References
2020
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Optimal_design Retrieved:2020-9-15.
- In the design of experiments, optimal designs (or optimum designs [1] ) are a class of experimental designs that are optimal with respect to some statistical criterion. The creation of this field of statistics has been credited to Danish statistician Kirstine Smith.
In the design of experiments for estimating statistical models, optimal designs allow parameters to be estimated without bias and with minimum variance. A non-optimal design requires a greater number of experimental runs to estimate the parameters with the same precision as an optimal design. In practical terms, optimal experiments can reduce the costs of experimentation.
The optimality of a design depends on the statistical model and is assessed with respect to a statistical criterion, which is related to the variance-matrix of the estimator. Specifying an appropriate model and specifying a suitable criterion function both require understanding of statistical theory and practical knowledge with designing experiments.
- In the design of experiments, optimal designs (or optimum designs [1] ) are a class of experimental designs that are optimal with respect to some statistical criterion. The creation of this field of statistics has been credited to Danish statistician Kirstine Smith.
- ↑ The adjective "optimum" (and not "optimal") "is the slightly older form in English and avoids the construction 'optim(um) + al´—there is no 'optimalis' in Latin" (page x in Optimum Experimental Designs, with SAS, by Atkinson, Donev, and Tobias).