Submitted

  • K. Koňasová, J. Dvořák (2021+): Supervised nonparametric classification in the context of replicated point patterns. Submitted.
  • J. Dvořák, T. Mrkvička, J. Mateu, J.A. González (2021+): Nonparametric testing of the dependence structure among points-marks-covariates in spatial point patterns. Submitted. Preprint available at ArXiv.org.
  • S. Nagy, J. Dvořák (2021+): Robust depth-based inference in elliptical models. To appear in the book of short papers in the Springer Series “Studies in Classification, Data Analysis and Knowledge Organization” devoted to the CLADAG 2019 meeting.

2021

  • K. Koňasová, J. Dvořák (2021): Techniques from functional data analysis adaptable for spatial point patterns, in Proceedings of the 22nd European Young Statisticians Meeting (eds. A. Makridis, F.S. Milienos, P. Papastamoulis, C. Parpoula & A. Rakitzis), Athens, Panteion University of Social and Political Sciences, 56-60. Proceedings website.
  • J. Vondráček, J. Dvořák (2021): A cautionary note on the variance of empirical pair correlation function. STAT 10(1), e406. Journal website.
  • J. Dvořák, T. Mrkvička (2021): Graphical tests of independence for general distributions. Computational Statistics. Journal website. Preprint available at ArXiv.org.
  • K. Koňasová, J. Dvořák (2021): Stochastic reconstruction for inhomogeneous point patterns. Methodology and Computing in Applied Probability 23, 527–547. Abstract. Journal website and full-text view-only version. Supplementary materials available here.
  • M. Ghorbani, N. Vafaei, J. Dvořák, M. Myllymäki (2021): Testing the first-order separability hypothesis for spatio-temporal point patterns. Computational Statistics and Data Analysis 161, 107245. Journal website. Preprint available at ArXiv.org.
  • T. Mrkvička, J. Dvořák, J.A. González, J. Mateu (2021): Revisiting the random shift approach for testing in spatial statistics. Spatial Statistics 42, 100430. Abstract. Journal website. Preprint available at ArXiv.org.
  • S. Nagy, J. Dvořák (2021): Illumination depth. Journal of Computational and Graphical Statistics 30(1), 78-90. Journal website. Preprint available at ArXiv.org.
  • M. Petráková, J. Dvořák (2021): Využití chí-kvadrát testů v prostorové statistice, Informační Bullentin České statistické společnosti, 32(1), 3-16.

2020

  • J. Dvořák, Š. Hudecová, S. Nagy (2020): Clover plot: Versatile visualisation in nonparametric classification. Statistical Analysis and Data Mining 13(6), 548-564. Journal website.
  • O. Zeman, J. Dvořák (2020): Neúplné vzorky z Poissonova rozdělení, Informační Bullentin České statistické společnosti, 31(3), 3-15.

2019

  • J. Dvořák, J. Møller, T. Mrkvička, S. Soubeyrand (2019): Quick inference for log Gaussian Cox processes with non-stationary underlying random fields. Spatial Statistics 33, 100388. Abstract. Journal website. Preprint available at ArXiv.org.
  • S. Nagy, J. Dvořák (2019): Illumination in depth analysis. In G.C. Porzio, F. Greselin, and S. Balzano (eds.) CLADAG 2019. Book of Short Papers, 353-356. Università di Cassino e del Lazio Meridionale.
  • J. Dvořák (2019): Proč jsou logaritmické tabulky nejohmatanější na začátku? Pokroky matematiky, fyziky a astronomie 64(1), 14-28.
  • J. Dvořák, M. Snětinová (2019): Bertrandův paradox aneb není náhoda jako náhoda. Rozhledy matematicko-fyzikální 94(2), 12-17.

2018

  • J. Dvořák, J. Švihlík, J. Kybic, B. Radochová, J. Janáček, J. Kukal, J. Borovec, D. Habart (2018): Volume estimation from single images: an application to pancreatic islets. Image Analysis and Stereology 37 (3), 191-204. Abstract. Journal website.

2017

  • J. Dvořák (2017): O dětech, čápech a kauzalitě. Pokroky matematiky, fyziky a astronomie 62(4), 264-274.
  • M. Prokešová, J. Dvořák, E.B.V. Jensen (2017): Two-step estimation procedures for inhomogeneous shot-noise Cox processes. Annals of the Institute of Statistical Mathematics 69 (3), 513-542. Abstract. Journal website.
  • J. Švihlík, J. Kybic, D. Habart, H. Hlushak, J. Dvořák, B. Radochová (2016): Langerhans islet volume estimation from 3D optical projection tomography. Chapter in Computer Vision – ACCV 2016 Workshops; ACCV 2016 International Workshops, Taipei, Taiwan, November 20-24, 2016, Revised Selected Papers, Part II, 583-594.

2016

  • J. Dvořák, M. Prokešová (2016): Parameter estimation for inhomogeneous space-time shot-noise Cox point processes. Scandinavian Journal of Statistics 43 (4), 939-961. Abstract. Journal website.
  • J. Dvořák, J. Švihlík, D. Habart, J. Kybic (2016): Comparison of volume estimation methods for pancreatic islet cells, in Proceedings of SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging. DOI: 10.1117/12.2216783. Abstract. Proceedings website.
  • J. Dvořák, M. Prokešová (2016): Asymptotic properties of the minimum contrast estimators for projections of inhomogeneous space-time shot-noise Cox processes. Applications of Mathematics 61 (4), 387-411. Abstract.
  • A. Pidnebesna, K. Helisová, J. Dvořák, R. Lechnerová, T. Lechner (2016): Statistical analysis and modelling of submissions to municipalities in the Czech Republic. Informační Bullentin České statistické společnosti (Information Bullentin of the Czech statistical society), 27 (4), 1-18. Abstract. Available online.

2015

  • J. Dvořák (2015): Model fitting for space-time point patterns using projection processes, in Proceedings of the 19th European Young Statisticians Meeting (ed. S. Nagy), Prague, Matfyzpress, 34-39. Abstract. Available online.

2014

  • J. Dvořák (2014): Statistical inference for spatial and space-time Cox point processes. Ph.D. thesis, Faculty of Mathematics and Physics, Charles University in Prague. Abstract.
  • M. Prokešová, J. Dvořák (2014): Statistics for inhomogeneous space-time shot-noise Cox processes. Methodology and Computing in Applied Probability 16 (2), 433-449. Abstract. Journal website.

2013

  • J. Boldyš, J. Dvořák, O. Bělohlávek, M. Skopalová (2013): Monte Carlo simulation of PET images for injection dose optimization. International Journal for Numerical Methods in Biomedical Engineering 29 (9), 988-999. Abstract. Journal website.
  • J. Dvořák, J. Boldyš, O. Bělohlávek, M. Skopalová (2013): Application of the random field theory in PET imaging - injection dose optimization. Kybernetika 49 (2), 280-300. Abstract. Available online.
  • J. Dvořák, E.B.V. Jensen (2013): On semi-automatic estimation of surface area. Journal of Microscopy 250 (2), 142-157. Available online as a research report of the CSGB centre. Abstract. Journal website.

2012

  • J. Dvořák, M. Prokešová (2012): Moment estimation methods for stationary spatial Cox processes - a comparison. Kybernetika 48 (5), 1007-1026. Available online. Report presenting complete results of the simulation study presented in the paper is available here. Abstract.
  • E. Čadková, M. Komárek, R. Kaliszová, V. Koudelková, J. Dvořák, A. Vaněk (2012): Sorption of Tebuconazole onto Selected Soil Minerals and Humic Acids. Journal of Environmental Science and Health Part B-Pesticides, Food Contaminants, and Agricultural Wastes 47, 336-342. Abstract. Journal website.

2011

  • J. Dvořák (2011): On moment estimation methods for spatial Cox processes, in WDS'11 Proceedings of Contributed Papers: Part I - Mathematics and Computer Sciences (eds. J. Šafránková and J. Pavlů), Prague, Matfyzpress, 31-36. Abstract.
  • J. Boldyš, J. Dvořák, O. Bělohlávek, M. Skopalová (2011): Monte Carlo simulation of PET images for injection dose optimization. Computational Vision and Medical Image Processing: VipIMAGE 2011. Editors J.M.R.S. Tavares and R.M. Natal Jorge. Taylor and Francis, London. Abstract.

2009

  • J. Dvořák, P. Kříž, V. Skubanič (2009): Simulace jednofrontového systému GI/GI/N v programu R (Simulation of a single queue system GI/GI/N in the R environment), Informační Bullentin České statistické společnosti (Information Bullentin of the Czech statistical society), 20 (3), p. 1-12. Abstract. Available online.