arbiter
JournalsAccount

Optimal Exact Designs of Multiresponse Experiments Under Linear and Sparsity Constraints

Lenka Filová et al.

Applied Stochastic Models in Business and Industry2026https://doi.org/10.1002/asmb.70072article
ABDC B
Weight
0.50

Abstract

We propose a computational approach to constructing exact designs on finite design spaces that are optimal for multiresponse regression experiments under a combination of the standard linear and specific ‘sparsity’ constraints. The linear constraints address, for example, limits on multiple resource consumption and the problem of optimal design augmentation, while the sparsity constraints control the set of distinct trial conditions utilized by the design. The key idea is to construct an artificial optimal design problem that can be solved using any existing mathematical programming technique for univariate‐response optimal designs under pure linear constraints. The solution to this artificial problem can then be directly converted into an optimal design for the primary multivariate‐response setting with combined linear and sparsity constraints. We demonstrate the utility and flexibility of the approach through a dose‐response case study with multivariate responses that sequentially adds constraints on safety, efficacy, and cost, where cost also depends on the number of distinct doses used.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1002/asmb.70072

Or copy a formatted citation

@article{lenka2026,
  title        = {{Optimal Exact Designs of Multiresponse Experiments Under Linear and Sparsity Constraints}},
  author       = {Lenka Filová et al.},
  journal      = {Applied Stochastic Models in Business and Industry},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/asmb.70072},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Optimal Exact Designs of Multiresponse Experiments Under Linear and Sparsity Constraints

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.