Published

  1. Hendrych, F., and Nagy, S. (2022). A note on the convergence of lift zonoids of measures. Stat. To appear.
  2. Nagy, S., Laketa, P., and Dyckerhoff, R. (2021). Angular halfspace depth: computation. In Giovanni C. Porzio, Carla Rampichini, and Chiara Bocci, editors, CLADAG 2021. Book of Abstracts and Short Papers, pages 169-172. Firenze University Press.
  3. Demni, H., Buttarazzi, D., Nagy, S., and Porzio, G. C. (2021). Angular halfspace depth: classification using spherical bagdistances. In Giovanni C. Porzio, Carla Rampichini, and Chiara Bocci, editors, CLADAG 2021. Book of Abstracts and Short Papers, pages 316-319. Firenze University Press.
  4. Laketa, P. and Nagy, S. (2021). Angular halfspace depth: central regions. In Giovanni C. Porzio, Carla Rampichini, and Chiara Bocci, editors, CLADAG 2021. Book of Abstracts and Short Papers, pages 356-359. Firenze University Press.
  5. Laketa, P., and Nagy, S. (2021). Halfspace depth for general measures: The ray basis theorem and its consequences. Statistical Papers. To appear.
  6. Helander, S., Laketa, P., Ilmonen, P., Nagy, S., Van Bever, G., and Viitasaari, L. (2021). Integrated shape-sensitive functional metrics. Journal of Multivariate Analysis. To appear.
  7. Rataj, J. (2021). Mean Euler characteristic of stationary random closed sets. Stochastic Processes and their Applications. To appear.
  8. Ferraty, F., and Nagy. S. (2021). Scalar-on-function local linear regression and beyond. Biometrika. To appear.
  9. Vencálek, O. and Hlubinka, D. (2021). A depth-based modification of the k-nearest neighbour method. Kybernetika, 57 (1), 15-37.
  10. Laketa, P., and Nagy, S. (2021). Reconstruction of atomic measures from their halfspace depth. Journal of Multivariate Analysis, 183, 104727.
  11. Dyckerhoff, R., and Mozharovskyi, P., and Nagy, S. (2021). Approximate computation of projection depths. Computational Statistics & Data Analysis, 157, 107166.
  12. Nagy, S., Helander, S., Van Bever, G., Viitasaari, L., and Ilmonen, P. (2021). Flexible integrated functional depths. Bernoulli, 27(1), 673-701.
  13. Nagy, S. and Dvořák, J. (2020). Robust depth-based inference in elliptical models. In: Balzano S., Porzio G. C., Salvatore R., Vistocco D., Vichi M. (eds) Statistical Learning and Modeling in Data Analysis - Methods and Applications. To appear. Studies in Classification, Data Analysis and Knowledge Organization. Springer.
  14. Nagy, S., Dyckerhoff, R., and Mozharovskyi, P. (2020). Uniform convergence rates for the approximated halfspace and projection depth. Electronic Journal of Statistics, 14 (2), 3939-3975.
  15. Dvořák, J., Hudecová, Š., and Nagy, S. (2020). Clover plot: Versatile visualisation in nonparametric classification. Statistical Analysis and Data Mining, 13, 548-564.
  16. Patáková, Z., Tancer, M., and Wagner, U. (2020). Barycentric cuts through a convex body. 36th International Symposium on Computational Geometry (SoCG 2020), 62:1--62:16.
  17. de Mesmay, A., Rieck, Y., Sedgwick, E., and Tancer, M. (2021). The unbearable hardness of unknotting. Advances in Mathematics. To appear.
  18. Nagy, S. and Dvořák, J. (2021). Illumination depth. Journal of Computational and Graphical Statistics, 30 (1), 78-90.
  19. Aichholzer, O., Balko, M., Hackl, T., Kynčl, J., Parada, I., Scheucher, M., Valtr P., and Vogtenhuber, B. (2020). A superlinear lower bound on the number of 5-holes. Journal of Combinatorial Theory, Series A 173, 105236.
  20. Kynčl, J. (2020). Simple realizability of complete abstract topological graphs simplified. Discrete and Computational Geometry 64(1), 1-27.
  21. Balko, M., Scheucher, M., and Valtr, P. (2020). Holes and islands in random point sets. 36th International Symposium on Computational Geometry (SoCG 2020), 14:1--14:16.
  22. Nagy, S. (2020). Scatter halfspace depth: Geometric insights. Applications of Mathematics, 65, 287–298.
  23. Nagy, S. (2020). Depth in infinite-dimensional spaces. In: Aneiros G., Horová I., Hušková M., Vieu P. (eds) Functional and High-Dimensional Statistics and Related Fields. IWFOS 2020, pages 187-195. Contributions to Statistics. Springer, Cham
  24. Nagy, S. (2020). The halfspace depth characterization problem. In: La Rocca M., Liseo B., Salmaso L. (eds) Nonparametric Statistics. ISNPS 2018, 379-389. Springer Proceedings in Mathematics & Statistics, vol 339. Springer, Cham.
  25. Nagy, S. (2019). Halfspace depth does not characterize probability distributions. Statistical Papers. To appear.
  26. Nagy, S. and Dvořák, J. (2019). Illumination in depth analysis. In Giovanni C. Porzio, Francesca Greselin, and Simona Balzano, editors, CLADAG 2019. Book of Short Papers, 353-356. Università di Cassino e del Lazio Meridionale.
  27. Nagy, S., Schütt, C., and Werner, E. (2019). Halfspace depth and floating body. Statistics Surveys, 13, 52-118.
  28. Nagy, S. (2019). Scatter halfspace depth for K-symmetric distributions. Statistics & Probability Letters, 149, 171-177.
  29. Fulek, R. and Kyncl, J. (2019). Z2-genus of graphs and minimum rank of partial symmetric matrices. Proceedings of the 35th International Symposium on Computational Geometry (SoCG 2019), Leibniz International Proceedings in Informatics (LIPIcs) 129, 39:1-39:16, Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik.
  30. de Mesmay, A., Rieck, Y., Sedgwick, E., and Tancer, M. (2019). The unbearable hardness of unknotting. Proceedings of the 35th International Symposium on Computational Geometry (SoCG 2019), Leibniz International Proceedings in Informatics (LIPIcs) 129, 49:1–49:19, Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik.
  31. Balko, M., Bhore, S., Martínez-Sandoval, L., and Valtr, P. (2019). On Erdős–Szekeres-type problems for k-convex point sets. In the Proceedings of the 30th International Workshop on Combinatorial Algorithms (IWOCA 2019), Lecture Notes in Computer Science, vol 11638. Springer, Cham, 35–47.
  32. Nagy, S. and Ferraty, F. (2018). Data depth for measurable noisy random functions. Journal of Multivariate Analysis, 170, 95-114.

Under review

  1. Hallin, M., Hlubinka, D., and Hudecová, Š. (2020). Fully distribution-free center-outward rank tests for multiple-output regression and MANOVA. arXiv:2007.15496
  2. Laketa, P. and Nagy, S. (2020). Halfspace depth for general measures: The ray basis theorem and its consequences.
  3. Balko, M., Scheucher, M., and Valtr, P. (2020). Tight bounds on the expected number of holes in random point sets.
  4. Balko, M., Chodounský, D., Hubička, J., Konečný, M., and Vena, L. (2020). Big Ramsey degrees of 3-uniform hypergraphs are finite arXiv:2008.00268
  5. Balko, M., Scheucher, M., and Valtr, P. (2020). Holes and islands in random point sets. arXiv:2003.00909
  6. Hlubinka, D., Kotík, L., and Šiman, M. (2019). Multivariate quantiles with both overall and directional probability interpretation.
  7. Kyncl, J. (2019). Simple realizability of complete abstract topological graphs simplified. arXiv:1608.05867.
  8. Balko, M., Bhore, S., Martínez-Sandoval, L., and Valtr, P. (2019). On Erdős–Szekeres-type problems for k-convex point sets (full version).
  9. Paták, P. and Tancer, M. (2018). Embeddings of k-complexes into 2k-manifolds. arXiv:1904.02404