Removing inessential points in c-and A-optimal design
| Autor: | Guillaume Sagnol, Luc Pronzato |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Optimal design Mathematical optimization Screening test Optimization algorithm Applied Mathematics 05 social sciences Multiplicative function 01 natural sciences 010104 statistics & probability 0502 economics and business 0101 mathematics Statistics Probability and Uncertainty Equivalence (formal languages) Design space Support point 050205 econometrics Cone programming Mathematics |
| Zdroj: | Journal of Statistical Planning and Inference. 213:233-252 |
| ISSN: | 0378-3758 |
| DOI: | 10.1016/j.jspi.2020.11.011 |
| Popis: | A design point is inessential when it does not contribute to an optimal design, and can therefore be safely discarded from the design space. We derive three inequalities for the detection of such inessential points in c-optimal design: the first two are direct consequences of the equivalence theorem for c-optimality; the third one is derived from a second-order cone programming formulation of c-optimal design. Elimination rules for A-optimal design are obtained as a byproduct. When implemented within an optimization algorithm, each inequality gives a screening test that may provide a substantial acceleration by reducing the size of the problem online. Several examples are presented with a multiplicative algorithm to illustrate the effectiveness of the approach. |
| Databáze: | OpenAIRE |
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