## Software for Optimal Design## by the experimental design group from Comenius University |
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University Faculty R.Harman L.Filova S.Rosa |
## R library OptimalDesign- The library OptimalDesign
enables the user to easily compute D-, A-, I-, and c-efficient designs of experiments including:
- optimal approximate and exact designs with or without replications,
- optimal designs at standard or restricted design spaces,
- optimal designs under various kinds of simultaneous constraints, ...
- The library is free, including the free academic license for the few functions that require the commercial gurobi solver; see our gurobi installation guide. (Note that most of the computational procedures in the library OptimalDesign are open source and do not require the gurobi solver.)
- Many of the implemented algorithms have been developed by the authors of OptimalDesign themselves and substantially outperform competing methods and/or allow for solving more complex design problems.
- See a brief introduction including mathematical specifications.
- OptimalDesign can also be used to compute the solutions to some related optimization problems such as minimum-volume data-enclosing ellipsoids and t-optimal graphs.
- The package is actively maintained, continually tested and improved by the authors. See the list of known bugs and suggestions for improvement.
- We will be happy to help you with any technical or theoretical problem, or with any question related to the computation of experimental designs.
## Computer source codes accompanying our academic papers- Harman R, Rosa S (2023): Mixed-integer linear programming for computing optimal experimental designs, submitted (see the arXiv preprint for a preliminary version).
- Harman R, Filová L, Rosa S (2021): Optimal Design of Multifactor Experiments via Grid Exploration,
*Statistics and Computing*, Volume 31, 70 (see the arXiv preprint for a preliminary version). - Filová L, Harman R (2020): Ascent with Quadratic Assistance for the Construction of Exact Experimental Designs,
*Computational Statistics*, Volume 35, pp. 775–801 DOI, rdcu (pre-print: arXiv) - Harman R, Filová L, Richtárik P (2020): A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments,
*Journal of the American Statistical Association*, Volume 115, pp. 348-361 DOI (pre-print: arXiv)- od-REX-D.r (od-REX-D.txt): The original R version as used in the manuscript
- od-REX-A.r (od-REX-A.txt): The original R version as used in the manuscript
- Simple commented example of using REX
- The currently fastest R version of REX for D-optimality
- The currently fastest R version of REX for A- and I-optimality
- R Shiny application for computing D-, A- and I-optimal approximate designs with REX
- R Shiny application for computing minimum volume enclosing ellipsoids with REX
- Harman R, Benková E (2017): Barycentric algorithm for computing D-optimal size- and cost-constrained designs of experiments,
*Metrika*, Volume 80, pp. 201–225 DOI, rdcu- barycost.m (barycost.txt) for Matlab: Compute D-optimal approximate size-and-cost constrained designs of experiments.
- Harman R, Bachratá A, Filová L (2016): Construction of efficient experimental designs under multiple resource constraints,
*Applied Stochastic Models in Business and Industry*, Volume 32, pp. 3-17 DOI, arXiv (older version)- Hugo.m (Hugo.txt) for Matlab: Compute efficient exact designs of experiments under general linear resource constraints.
- Malab examples from the manuscript: Example1b.m (Example1b.txt), Example2.m (Example2.txt), Example3.m (Example3.txt).
- HugoR.r (HugoR.txt) for R: Compute exact designs of experiments under the standard (size) constraint on the number of trials.
- R example from the manuscript: Example1a.r (Example1a.txt).
- Benková E, Harman R, Müller WG (2016): Privacy sets for constrained space-filling,
*Journal of Statistical Planning and Inference*, Volume 171, pp. 1–9 DOI- Henry.m for Matlab - Experimental design optimization for "bridge" constraints and the D-optimality criterion
- Harman R, Filová L (2014): Computing efficient exact designs of experiments using integer quadratic programming,
*Computational Statistics & Data Analysis*, Volume 71, pp. 1159–1167 DOI- DQ_gurobi.m (DQ_gurobi.txt) for Matlab, using the Gurobi solver: Compute exact DQ-optimal designs of experiments under general linear constraints on the design weights.
- DQ_cplex.m (DQ_cplex.txt) for Matlab, using the Cplex solver: Compute exact DQ-optimal designs of experiments under general linear constraints on the design weights.
## Contact- E-mail: harman[at]fmph.uniba.sk
- Address:
Department of Applied Mathematics and Statistics Faculty of Mathematics, Physics and Informatics Comenius University Mlynská dolina 842 48 Bratislava 4 Slovak Republic
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