Radoslav Harman

publications and research activities


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Selected publications

  • Rosa S, Harman R (2022): Computing minimum-volume enclosing ellipsoids for large datasets, Computational Statistics & Data Analysis, Volume 171, 107452 DOI
  • Harman R, Filová L (2022): Základy pravdepodobnosti pre študentov informatiky a dátovej vedy (a textbook in Slovak), Vydavateľstvo FMFI UK, ISBN 978-80-8147-126-1, 109 s., online prístup
  • Rosa S, Harman R (2022): Maticová algebra pre štatistiku a dátovú vedu (a textbook in Slovak), Vydavateľstvo FMFI UK, ISBN 978-80-8147-109-4, 131 s., online prístup
  • Harman R, Filová L, Rosa S (2021): Optimal Design of Multifactor Experiments via Grid Exploration, Statistics and Computing, Volume 31, 70 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)
  • 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, Rosa S (2020): On greedy heuristics for computing D-efficient saturated subsets, Operations Research Letters, Volume 48, pp. 122-129 DOI (pre-print: arXiv)
  • Harman R, Müller W (2020): A design criterion for symmetric model discrimination based on flexible nominal sets, Biometrical Journal, Volume 62, pp. 1090-1104 DOI (pre-print: arXiv)
  • Koščová M, Harman R, Mačutek J (2020): Iterated partial summations applied to finite-support discrete distributions, Mathematica Slovaca, Volume 70, pp. 489-496 DOI
  • 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 DOI (pre-print: arXiv)
  • Harman R, Prus M (2018): Computing optimal experimental designs with respect to a compound Bayes risk criterion, Statistics & Probability Letters , Volume 137, pp. 135-141 DOI (pre-print: arXiv)
  • Rosa S, Harman R (2017): Optimal approximate designs for comparison with control in dose-escalation studies, Test, Volume 26, pp. 638-660 DOI (pre-print: arXiv)
  • 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 (pre-print: arXiv)
  • Rosa S, Harman R (2016): Optimal approximate designs for estimating treatment contrasts resistant to nuisance effects, Statistical Papers, Volume 57, pp. 1077–1106 DOI, rdcu (pre-print: arXiv)
  • 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
  • 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 (pre-print: arXiv)
  • Müller WG, Harman R, Benková E (2016): Discussion of "Space-filling designs for computer experiments: A review", Quality Engineering, Volume 28, pp. 36-38 DOI
  • Sagnol G, Harman R (2015): Computing exact D-optimal designs by mixed integer second-order cone programming, The Annals of Statistics, Volume 43, pp. 2198–2224 DOI (pre-print: arXiv)
  • Harman R, Sagnol G (2015): Computing D-Optimal Experimental Designs for Estimating Treatment Contrasts Under the Presence of a Nuisance Time Trend, In: Stochastic Models, Statistics and Their Applications, Springer Proceedings in Mathematics & Statistics, Volume 122, pp. 83-91 DOI
  • Sagnol G, Harman R (2015): Optimal Designs for Steady-State Kalman Filters, In: Stochastic Models, Statistics and Their Applications, Springer Proceedings in Mathematics & Statistics, Volume 122, pp. 149-157 DOI
  • Tučková M, Harman R, Tuček P, Tuček J (2014): Design of Experiment for Hysteresis Loops Measurement, Journal of Magnetism and Magnetic Materials, Volume 368, pp. 64-69 DOI
  • Harman R (2014): Multiplicative Methods for Computing D-Optimal Stratified Designs of Experiments, Journal of Statistical Planning and Inference, Volume 146, pp. 82-94 DOI
  • 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
  • Filová L, Harman R (2013): Criterion-robust Experimental Designs for the Quadratic Regression on a Square and a Cube, Communications in Statistics - Theory and Methods, Volume 42, pp. 2044-2055 DOI
  • Lacko V, Harman R (2012): A conditional distribution approach to uniform sampling on spheres and balls in Lp spaces, Metrika, Volume 75, pp. 939-951, DOI, rdcu
  • Filová L, Harman R (2012): Criterion-robust Designs for the Models of Spring Balance Weighing, Tatra Mountains Mathematical Publications, Volume 51, pp. 23–32, TMMP
  • Filová L, Trnovská M, Harman R (2012): Computing maximin efficient experimental designs using the methods of semidefinite programming, Metrika, Volume 75, pp. 709-719 DOI, rdcu
  • Amo-Salas M, Ortega-López V, Harman R, Alonso-Gonzáles A (2011): A New Model for Predicting the Flight Activity of Lobesia botrana (Lepidoptera: Tortricidae), Crop Protection, Volume 30, pp. 1586-1593 DOI
  • Harman R, Štulajter F (2011): Optimal sampling designs for the Brownian motion with a quadratic drift, Journal of Statistical Planning and Inference, Volume 141, pp. 2750–2758 DOI
  • Filová L, Harman R, Klein T (2011): Approximate E-optimal designs for the model of spring balance weighing with a constant bias, Journal of Statistical Planning and Inference, Volume 141, pp. 2480-2488 DOI
  • Harman R, Lacko V (2010): On decompositional algorithms for uniform sampling from n-balls and n-spheres, Journal of Multivariate Analysis, Volume 101, pp. 2297-2304 DOI
  • Harman R, Štulajter F (2010): Optimal prediction designs in finite discrete spectrum linear regression models, Metrika, Volume 72, pp. 281-294 DOI, rdcu
  • Harman R, Hönschová E, Somorčík J (2009): Zbierka úloh zo základov teórie pravdepodobnosti (A Collection of Exercises from Probability; a textbook in Slovak), PACI, ISBN 978-80-89186-53-2, 252 s. Info
  • Harman R, Trnovská M (2009): Approximate D-optimal designs of experiments on the convex hull of a finite set of information matrices, Mathematica Slovaca, Volume 59, pp. 693–704 DOI
  • Harman R, Štulajter F (2009): Optimality of equidistant sampling designs for a nonstationary Ornstein-Uhlenbeck process, In: Proceedings of the 6th St.Petersburg Workshop on Simulation, S.M.Ermakov, V.S.Melas, A.N.Pepelyshev (eds.), St. Petersburg 2009, pp. 1097-1101 pdf
  • Harman R, Jurík T (2008): Computing c-optimal experimental designs using the simplex method of linear programming, Computational Statistics & Data Analysis, Volume 53, pp. 247-254 DOI
  • Harman R (2008): Equivalence theorem for Schur optimality of experimental designs, Journal of Statistical Planning and Inference, Volume 138, pp. 1201-1209 DOI
  • Harman R, Pronzato L (2007): Improvements on removing non-optimal support points in D-optimum design algorithms, Statistics & Probability Letters, Volume 77, pp. 90-94 DOI (pre-print: arXiv)
  • Harman R (2004): Minimal efficiency of designs under the class of orthogonally invariant information criteria, Metrika, Volume 60, pp. 137-153 DOI, rdcu
  • Harman R (2004): Lower bounds on efficiency ratios based on Φp-optimal designs, In: Proceedings from the conference "mODa 7 - Advances in Model-Oriented Design and Analysis" (Heeze, Netherlands 2004), Physica-Verlag, pp. 89-96 DOI
  • Harman R (2004): Minimal efficiency of experimental designs under the class of orthogonally invariant criteria, PhD. Thesis, Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava. pdf
  • Harman R (2003): A method how to delete points which do not support a D-optimal design, Tatra Mountains Mathematical Publications, Volume 26, pp. 59-67 ps
  • Pavlásek J, Jenča J, Harman R (2003): Rate coding: neurobiological network performing detection of the difference between mean spiking rates, Acta Neurobiologiae Experimentalis, Volume 63, pp. 83-98 pdf
  • Harman R (1999): The asymptotic regularity of a generalization of a linear regression model with a nonmonotonous link function, Tatra Mountains Mathematical Publications, Volume 17, pp. 37–44 ps

Selected invited talks

  • Experiments for Processes With Time or Space Dynamics, Isaac Newton Institute for Mathematical Sciences, Cambridge, England, 2011 Website
  • Design and Analysis of Experiments, University of Georgia, Athens, USA, 2012 Website
  • Design and Analysis of Experiments in Healthcare, Isaac Newton Institute for Mathematical Sciences, Cambridge, England, 2015 Website
  • Designed Experiments: Recent Advances in Methods and Applications, University of Technology Sydney, Australia, 2015 Website
  • Conference on Experimental Design and Analysis, Academia Sinica, Taipei, Taiwan, 2016 Website
  • Latest Advances in the Theory and Applications of Design and Analysis of Experiments, Banff, Canada, 2017 Website
  • Design of Experiments: New Challenges, CIRM, France, 2018 Website
  • 5th International Conference on Design of Experiments, FedEx Institute of Technology, Memphis, USA, 2019 Website

Selected grants

  • 2013-2015 Principal investigator of the VEGA grant No. 1/0163/13 "Methods of optimal experimental design"
  • 2016-2018 Principal investigator of the VEGA grant No. 1/0521/16 "Methods of optimal experimental design"
  • 2019-2021 Principal investigator of the VEGA grant No. 1/0341/19 "Methods of optimal experimental design"
  • 2022-2024 Principal investigator of the VEGA grant No. 1/0362/22 "Methods of optimal experimental design"

Doctoral students

  • Lenka Filová: "Ek-optimal and maximin efficient designs of experiments"; def. 2010
  • Vladimír Lacko: "Design of experiments in stochastic dynamics"; def. 2014
  • Alena Bachratá: "Optimal design of block experiments"; def. 2015
  • Michaela Tučková: "Design of experiment for hysteresis loops measurement"; def. 2017
  • Samuel Rosa: "Optimal trend-resistant designs of experiments" def. 2018
  • Eva Benková: "Algorithms for computing optimal experimental designs under non-standard constraints"; def. 2022
FMFI UK