Samuel Rosa - research


Homepage

Publications

  • Rosa S. (2023): Toward more numerically stable computations of optimal experimental designs, Communications in Statistics - Simulation and Computation, Online first
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  • Rosa S., Kocianova A. (2023): Accuracy of critical gap estimates, Alexandria Engineering Journal, Volume 75, pp. 565-576
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  • Rosa S., Harman R. (2022): Computing minimum-volume enclosing ellipsoids for large datasets, Computational Statistics and Data Analysis, Volume 171, 107452
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  • Harman R., Filová L., Rosa S. (2021): Optimal design of multifactor experiments via grid exploration, Statistics and Computing, Volume 31, 70
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  • Rosa S. (2020): Optimal experimental designs for treatment contrasts in heteroscedastic models with covariates, Journal of Statistical Planning and Inference, Volume 209, pp. 280-291
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  • Harman R., Rosa S. (2020): On greedy heuristics for computing D-efficient saturated subsets, Operations Research Letters, Volume 48, pp. 122-129
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  • Ščevková J., Hrabovský M., Kováč J., Rosa S. (2019): Intradiurnal variation of predominant airborne fungal spore biopollutants in the Central European urban environment, Environmental Science and Pollution Research, Volume 26, pp. 34603–34612
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  • Rosa S. (2019): Equivalence of weighted and partial optimality of experimental designs, Metrika, Volume 82, pp. 719-732
    - link ; manuscript on arXiv; readcube
  • Rosa S. (2019): E- and R-optimality of block designs for treatment-control comparisons, Communications in Statistics - Theory and Methods, Volume 48, pp. 5233-5244
    - link; manuscript on arXiv
  • Harman R., Rosa S. (2019): Removal of the points that do not support an E-optimal experimental design, Statistics & Probability Letters, Volume 147, pp. 83-89
    - link; manuscript on arXiv
  • Rosa S. (2018): Optimal designs for treatment comparisons represented by graphs, AStA - Advances in Statistical Analysis, Volume 102, pp. 479-503
    - link; readcube; manuscript on arXiv
  • Rosa S., Harman R. (2017): Optimal approximate designs for comparison with control in dose-escalation studies, TEST, Volume 26, pp. 638–660.
    - link; manuscript on arXiv
  • Rosa S., Harman R. (2016): Optimal approximate designs for estimating treatment contrasts resistant to nuisance effects, Statistical Papers, Volume 57, pp. 1077–1106.
    - link; readcube; manuscript on arXiv

Contact

  • Address:
        Department of Applied Mathematics and Statistics
        Faculty of Mathematics, Physics and Informatics
        Comenius University
        Mlynská dolina
        842 48
  • E-mail: samuel.rosa[at]fmph.uniba.sk
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