Seznam publikací

Články

[29] B. Kriesche, A. Koubek, Z. Pawlas, V. Beneš, R. Hess, V. Schmidt (2016): On the computation of area probabilities based on a spatial stochastic model for precipitation cells and precipitation amounts, Stoch. Env. Res. Risk A., Online First, DOI: 10.1007/s00477-016-1321-8.

[28] M. Matsui, Z. Pawlas (2016): Fractional absolute moments of heavy tailed distributions, Braz. J. Prob. Stat., 30, 272--298.

[27] A. Koubek, Z. Pawlas, T. Brereton, B. Kriesche, V. Schmidt (2016): Testing the random field model hypothesis for random marked closed sets, Spat. Stat., 16, 118--136.

[25] D. Hug, G. Last, Z. Pawlas, W. Weil (2014): Statistics for Poisson models of overlapping spheres, Adv. in Appl. Probab. (SGSA), 46, 937--962.

[24] Z. Pawlas (2014): Self-crossing points of a line segment process, Meth. Comput. Appl. Probab., 16, 295--309.

[23] Z. Pawlas (2013): Estimating distribution of neuronal response latency, Informační Bulletin České statistické společnosti, 24, 89--100.

[22] L. Heinrich, Z. Pawlas (2013): Absolute regularity and Brillinger-mixing of stationary point processes, Lithuanian Math. J., 53, 293--310.

[21] Z. Pawlas (2012): Local stereology of extremes, Image Anal. Stereol., 31, 99--108.

[20] Z. Pawlas (2011): Estimation of summary characteristics from replicated spatial point processes, Kybernetika, 47, 880--892.

[19] T. Mikosch, Z. Pawlas, G. Samorodnitsky (2011): Large deviations for Minkowski sums of heavy-tailed generally non-convex random compact sets, Vestnik S.-Peterburg. Univ. Mat. Mekh. Astronom., 70--78.

[18] T. Mikosch, Z. Pawlas, G. Samorodnitsky (2011): A large deviation principle for Minkowski sums of heavy-tailed random compact convex sets with finite expectation, In New Frontiers in Applied Probability, A Festschrift for Søren Asmussen, P. Glynn, T. Mikosch and T. Rolski (eds.), J. Appl. Probab., 48A, 133--144.

[17] Z. Pawlas, P. Lansky (2011): Distribution of interspike intervals estimated from multiple spike trains observed in a short time window, Phys. Rev. E, 83, 011910.

[16] Z. Pawlas (2011): Estimation of interarrival time distribution from short time windows, Acta Univ. Carolin. Math. Phys. , 52, 59--67.

[15] Z. Pawlas, L. B. Klebanov, V. Beneš, M. Prokešová, J. Popelář, P. Lánský (2010): First-spike latency in the presence of spontaneous activity, Neural Comput., 22, 1675--1697.

[14] Z. Pawlas, O. Honzl (2010): Comparison of length-intensity estimators for segment processes, Statist. Probab. Lett., 80, 825--833.

[13] Z. Pawlas (2009): Empirical distributions in marked point processes, Stochastic Process. Appl., 119, 4194--4209.

[11] Z. Pawlas, J. R. Nyengaard (2009): Estimation of variance components of local stereological volume estimators: a pilot study, J. Microsc., 236, 60--69.

[10] Z. Pawlas, J. R. Nyengaard, E. B. Vedel Jensen (2009): Particle sizes from sectional data, Biometrics, 65, 216--224.

[9] Z. Pawlas, L. B. Klebanov, M. Prokop, P. Lansky (2008): Parameters of spike trains observed in a short time window, Neural Comput., 20, 1325--1343.

[8] L. Heinrich, Z. Pawlas (2008): Weak and strong convergence of empirical distribution functions from germ-grain processes, Statistics, 42, 49--65.

[4] Z. Pawlas, E. B. Vedel Jensen (2006): Further results on variances of local stereological estimators, Image Anal. Stereol., 25, 155--163.

[3] Z. Pawlas, L. Heinrich (2005): Nonparametric testing of distribution functions in germ-grain models, In Case Studies in Spatial Point Process Modeling, A. Baddeley, P. Gregori, J. Mateu, R. Stoica and D. Stoyan (eds.), Lecture Notes in Statistics, 185, 125--134, Springer, New York.

[2] Z. Pawlas, V. Beneš (2004): On the central limit theorem for the stationary Poisson process of compact sets, Math. Nachr., 267, 77--87.

[1] Z. Pawlas (2003): Central limit theorem for random measures generated by stationary processes of compact sets, Kybernetika, 39, 719--729.

Recenzované příspěvky ve sbornících

[26] B. Kriesche, A. Koubek, Z. Pawlas, V. Beneš, R. Hess, V. Schmidt (2015): A model-based approach to the computation of area probabilities for precipitation exceeding a certain threshold, Proceedings of the 21st International Congress on Modelling and Simulation (eds. T. Weber, M. J. McPhee, R. S. Anderssen), Modelling and Simulation Society of Australia and New Zealand, 2103--2109.

[12] Z. Pawlas (2009): Variance of local stereological volume estimators for dependent particles, ECS10: The 10th European Congress of Stereology and Image Analysis (eds. Vincenzo Capasso, Giacomo Aletti and Alessandra Micheletti), Progetto Leonardo, 526--531.

[7] Z. Pawlas (2006): Estimation of the distribution function in germ-grain models, Proceedings Prague Stochastics 2006 (eds. Marie Hušková and Martin Janžura), Matfyzpress, 579--589.

[6] Z. Pawlas, E. B. Vedel Jensen (2006): Some remarks on variances of local stereological volume estimators, Proceedings S4G (eds. Radka Lechnerová, Ivan Saxl and Viktor Beneš), Union of Czech Mathematicians and Physicists, 191--196.

[5] Z. Pawlas (2006): Estimation of the variance in marked point processes, Robust 2006 (eds. Jaromír Antoch a Gejza Dohnal), Jednota českých matematiků a fyziků, 245--252.

Nerecenzované příspěvky a abstrakty ve sbornících

Z. Pawlas (2011): Local stereology of extremes, Proceedings of the 13th International Congress for Stereology, Chinese Society for Stereology, Beijing.

Z. Pawlas, E. B. Vedel Jensen (2009): Estimation variances in local stereology, ISI 2009 Proceedings, International Statistical Institute, Beta Products, Durban.

L. Heinrich, Z. Pawlas (2004): Weak and strong convergence of empirical distribution functions in germ-grain models, Spatial Point Process Modelling and its Applications (eds. Adrian Baddeley, Pablo Gregori, Jorge Mateu, Radu Stoica and Dietrich Stoyan), University Jaume I, 101--124.

L. Heinrich, Z. Pawlas (2004): Weak and strong convergence of empirical distribution functions in germ-grain models, Proceedings of the 2nd International Workshop in Applied Probability, University of Piraeus, 180--183.

Z. Pawlas (2003): Central limit theorem for random measures generated by stationary processes of compact sets, Proceedings of 54th Session of the International Statistical Institute, Bulletin of the International Statistical Institute.

Z. Pawlas (2002): Central limit theorems in stochastic geometry, WDS'02 - Proceedings of Contributed Papers, Part I, Matfyzpress, Praha, 189--193.

Preprinty

Z. Pawlas (2009): Empirical distributions in marked point processes, KPMS Preprint 65, MFF UK, Praha.

O. Honzl, Z. Pawlas (2008): Estimator variance in Poisson segment processes, KPMS Preprint 63, MFF UK, Praha.

Z. Pawlas, J. R. Nyengaard, E. B. V. Jensen (2007): Particle sizes from sectional data, Thiele research report 1, University of Aarhus.

Z. Pawlas, E. B. V. Jensen (2005): Further results on variances of local stereological estimators, Thiele research report 11, University of Aarhus.

L. Heinrich, Z. Pawlas (2004): Asymptotic properties of Horvitz-Thompson type empirical distribution functions in germ-grain models and their applications, KPMS Preprint 36, MFF UK, Praha.

Citace

N. Ross, D. Schuhmacher (2017): Wireless network signals with moderately correlated shadowing still appear Poisson, IEEE Transactions on Information Theory, 63, 1177--1198. [22]

P. Alonso-Ruiz, E. Spodarev (2017): Estimation of entropy for Poisson marked point processes, Advances in Applied Probability, 49, 258--278. [13]

V. Benes, J. Vecera, B. Eltzner, C. Wollnik, F. Rehfeldt, V. Kralova, S. Huckemann (2017): Estimation of parameters in a planar segment process with a biological application, Image Analysis and Stereology, 36, 25--33. [24]

T. Trigano, Y. Sepulcre, Y. Ritov (2017): Sparse reconstruction algorithm for nonhomogeneous counting rate estimation, IEEE Transactions on Signal Processing, 65, 372--385. [9]

D. Gervini (2016): Independent component models for replicated point processes, Spatial Statistics, 18, 474--488. [20]

C. Redenbach, J. Ohser, A. Moghiseh (2014): Second-order characteristics of the edge system of random tessellations and the PPI value of foams, Methodology and Computing in Applied Probability, 18, 59--79. [22]

C. A. N. Biscio, F. Lavancier (2016): Brillinger mixing of determinantal point processes and statistical applications, Electronic Journal of Statistics, 10, 582--607. [22]

S. Martínez, W. Nagel (2016): The β-mixing rate of STIT tessellations, Stochastics, 88, 396--414. [22]

M. Levakova, M. Tamborrino, L. Kostal, P. Lansky (2016): Presynaptic spontaneous activity enhances the accuracy of latency coding, Neural Computation, 28, 2162--2180. [15]

M. Levakova (2016): Effect of spontaneous activity on stimulus detection in a simple neuronal model, Mathematical Biosciences and Engineering, 13, 551--568. [15]

J. Večeřa, V. Beneš (2016): Interaction processes for unions of facets, the asymptotic behaviour with increasing intensity, Methodology and Computing in Applied Probability, 18, 1217--1239. [24]

A. Noorafshan, M. Motamedifar, S. Karbalay-Doust (2016): Estimation of the cultured cellsż volume and surface area: application of stereological methods on Vero cells infected by rubella virus, Iranian Journal of Medical Sciences, 41, 37--43. [10]

M. Levakova, M. Tamborrino, S. Ditlevsen, P. Lansky (2015): A review of the methods for neuronal response latency estimation, Biosystems, 136, 23--34. [15]

M. Kivelä, M. A. Porter (2015): Estimating interevent time distributions from finite observation periods in communication networks, Physical Review E, 92, 052813. [17]

C. Schauer, T. Tong, H. Petitjean, T. Blum, S. Beron, O. Mai, F. Schmitz, U. Boehm, T. Leinders-Zufall (2015): Hypothalamic gonadotropin-releasing hormone (GnRH) receptor neurons fire in synchrony with the female reproductive cycle, Journal of Neurophysiology, 114, 1008--1021. [15]

M. C. Tuten, A. Sánchez Meador, P. Z. Fulé (2015): Ecological restoration and fine-scale forest structure regulation in southwestern ponderosa pine forests, Forest Ecology and Management, 348, 57--67. [20]

Z. Cao, L. Cheng, C. Zhou, N. Gu, X. Wang, M. Tan (2015): Spiking neural network-based target tracking control for autonomous mobile robots, Neural Computing and Applications, 26, 1839--1847. [9]

L. Heinrich (2015): Gaussian limits of empirical multiparameter K-functions of homogeneous Poisson processes and tests for complete spatial randomness, Lithuanian Mathematical Journal, 55, 72--90. [8]

L. Heinrich, S. Klein (2014): Central limit theorems for empirical product densities of stationary point processes, Statistical Inference for Stochastic Processes, 17, 121--138. [22]

L. Heinrich, S. Lück, V. Schmidt (2014): Asymptotic goodness-of-fit tests for the Palm mark distribution of stationary point processes with correlated marks, Bernoulli, 20, 1673--1697. [8, 13]

L. Anton-Sanchez, C. Bielza, A. Merchan-Perez, J.-R. Rodriguez, J. DeFelipe, P. Larranaga (2014): Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis, Frontiers in Neuroanatomy, 8, 85. [20]

P. Calka, N. Chenavier (2014): Extreme values for characteristic radii of a Poisson-Voronoi tessellation, Extremes, 17, 359--385. [21]

J.-C. Pinoli (2014): Mathematical Foundations of Image Processing and Analysis, Volume 2, Wiley. [21]

J.-C. Pinoli (2014): Mathematical Foundations of Image Processing and Analysis, Volume 1, Wiley. [21]

M. Levakova, S. Ditlevsen, P. Lansky (2014): Estimating latency from inhibitory input, Biological Cybernetics, 108, 475--493. [15]

L. Heinrich, S. Klein, M. Moser (2014): Empirical mark covariance and product density function of stationary marked point processes -- a survey on asymptotic results, Methodology and Computing in Applied Probability, 16, 283--293. [8, 13]

J. Staněk, O. Šedivý, V. Beneš (2014): On random marked sets with a smaller integer dimension, Methodology and Computing in Applied Probability, 16, 397--410. [13]

E. B. Vedel Jensen, J. F. Ziegel (2014): Local stereology of tensors of convex bodies, Methodology and Computing in Applied Probability, 16, 263--282. [10]

J. Burguet, P. Andrey (2014): Statistical comparison of spatial point patterns in biological imaging, PLOS ONE, 9, e87759. [20]

S. Koyama, L. Kostal (2014): The effect of interspike interval statistics on the information gain under the rate coding hypothesis, Mathematical Biosciences and Engineering, 11, 63--80. [9]

K. Rajdl, P. Lansky (2014): Fano factor estimation, Mathematical Biosciences and Engineering, 11, 105--123. [9]

C. Kopp, I. Molchanov (2014): Large deviations for heavy-tailed random elements in convex cones, Journal of Mathematical Analysis and Applications, 411, 271--280. [18, 19]

F. M. Schaller, S. C. Kapfer, M. E. Evans, M. J. F. Hoffmann, T. Aste, M. Saadatfar, K. Mecke, G. W. Delaney, G. E. Schröder-Turk (2013): Set Voronoi diagrams of 3D assemblies of aspherical particles, Philosophical Magazine, 93, 3993--4017. [25]

R. Melendez-Perez, M. E. Rosas-Mendoza, R. R. Velazquez-Castillo, J. L. Arjona-Roman (2013): Determination of structural damage during slow freezing in pork cuts (longissimus dorsi), International Journal of Advanced Research in Engineering and Technology (IJARET), 4, 10--19. [10]

R. Lachièze-Rey, G. Peccati (2013): Fine Gaussian fluctuations on the Poisson space II: rescaled kernels, marked processes and geometric U-statistics, Stochastic Processes and their Applications, 123, 4186--4218. [24]

R. Ramezan, P. Marriott, S. Chenouri (2013): Multiscale analysis of neural spike trains, Statistics in Medicine, 33, 238--256. [15]

M. Uzuntarla, R. Uzun, E. Yilmaz, M. Ozer, M. Perc (2013): Noise-delayed decay in the response of a scale-free neuronal network, Chaos, Solitons & Fractals, 56, 202--208. [15]

O. Thorisdottir, M. Kiderlen (2013): Wicksell's problem in local stereology, Advances in Applied Probability (SGSA), 45, 925--944. [21]

O. Šedivý, J. Staněk, B. Kratochvílová, V. Beneš (2013): Sliced inverse regression and independence in random marked sets with covariates, Advances in Applied Probability (SGSA), 45, 626--644. [1]

H. Wang, Y. Chen, Y. Chen (2013): First-spike latency in Hodgkin's three classes of neurons, Journal of Theoretical Biology, 328, 19--25. [15]

M. Tamborrino, S. Ditlevsen, P. Lansky (2013): Parametric inference of neuronal response latency in presence of a background signal, Biosystems, 112, 249--257. [15]

R. A. Davis, T. Mikosch, Y. W. Zhao (2013): Measures of serial extremal dependence and their estimation, Stochastic Processes and their Applications, 123, 2575--2602. [18, 19]

M. J. West (2013): Local estimators of size in stereological studies, Cold Spring Harbor Protocols, 8, 719--726. [11]

L. Kostal, P. Lansky (2013): Information capacity and its approximations under metabolic cost in a simple homogeneous population of neurons, BioSystems, 112, 265--275. [9]

L. Kostal, P. Lansky, M. D. McDonnell (2013): Metabolic cost of neuronal information in an empirical stimulus-response model, Biological Cybernetics, 107, 355--365. [9]

L. Heinrich (2013): Asymptotic methods in statistics of random point processes, In: Stochastic Geometry, Spatial Statistics and Random Fields, E. Spodarev (ed.), Lecture Notes in Mathematics, 2068, pp. 115--150, Springer, Berlin. [8, 13]

L. Sacerdote, M. T. Giraudo (2013): Stochastic integrate and fire models: A review on mathematical methods and their applications, In: Stochastic Biomathematical Models, M. Bachar, J. J. Batzel, S. Ditlevsen (eds.), Lecture Notes in Mathematics, 2058, pp. 99--148, Springer, Berlin. [9]

O. Pokora, P. Lansky (2012): Estimating individual firing frequencies in a multiple spike train record, Journal of Neuroscience Methods, 211, 191--202. [17]

M. Tamborrino, S. Ditlevsen, P. Lansky (2012): Identification of noisy response latency, Physical Review E, 86, 021128. [15]

A. J. Larson, K. C. Stover, C. R. Keyes (2012): Effects of restoration thinning on spatial heterogeneity in mixed-conifer forest, Canadian Journal of Forest Research, 42, 1505--1517. [20]

L. Kostal, O. Pokora (2012): Nonparametric estimation of information-based measures of statistical dispersion, Entropy, 14, 1221--1233. [17]

M. Uzuntarla, M. Ozer, D. Q. Guo (2012): Controlling the first-spike latency response of a single neuron via unreliable synaptic transmission, European Physical Journal B, 85, 282. [15]

S. Ditlevsen, P. Lansky (2011): Firing variability is higher than deduced from the empirical coefficient of variation, Neural Computation, 23, 1944--1966. [9]

F. G. Lin, R. C. Liu (2010): Subset of thin spike cortical neurons preserve the peripheral encoding of stimulus onsets, Journal of Neurophysiology, 104, 3588--3599. [15]

A. Busciglio, F. Grisafi, F. Scargiali, A. Brucato (2010): On the measurement of bubble size distribution in gas-liquid contactors via light sheet and image analysis, Chemical Engineering Science, 65, 2558--2568. [10]

S. Ikeda, J. H. Manton (2009): Capacity of a single spiking neuron, International Workshop on statistical-mechanical informatics 2009 (IW-SMI 2009), J. Phys.: Conf. Ser., 197, 012014. [9]

S. Ikeda, J. H. Manton (2009): Capacity of a single spiking neuron channel, Neural Computation, 21, 1714--1748. [9]

A. Micheletti, P. M. V. Rancoita (2009): Estimators of the intensity of stationary planar fibre processes, Stereology and Image Analysis, ECS10, The 10th European Congress of ISS (eds. Vincenzo Capasso, Giacomo Aletti and Alessandra Micheletti), Progetto Leonardo, 131--136. [1]

P. Lansky, S. Ditlevsen (2008): A review of the methods for signal estimation in stochastic diffusion leaky integrate-and-fire neuronal models, Biological Cybernetics, 99, 253--262. [9]

S. Kötzer (2006): Geometric identities in stereological particle analysis, Image Analysis and Stereology, 25, 63--74. [4]

S. Böhm, L. Heinrich, V. Schmidt (2004): Asymptotic properties of estimators for the volume fractions of jointly stationary random sets, Statistica Neerlandica, 58, 388--406. [8]

V. Beneš, J. Rataj (2004): Stochastic Geometry - Selected Topics, Kluwer Academic Publishers, Boston. [2]

Další práce

Z. Pawlas (2013): Limit theorems for geometric models, habilitační práce, MFF UK, Praha.

Z. Pawlas (2004): Asymptotics in Stochastic Geometry, doktorská disertační práce, MFF UK, Praha.

Z. Pawlas (2001): Principy invariance ve stochastické geometrii, diplomová práce, MFF UK, Praha.

Z. Pawlas (2001): Centrální limitní věty ve stochastické geometrii, soutěžní práce SVOČ, MFF UK, Praha.

Pikomat

Z. Pawlas (2015): Pikomat MFF UK 2014-15: ročenka 30. ročníku, Matfyzpress, Praha.

Z. Pawlas (2014): Pikomat MFF UK 2013-14: ročenka 29. ročníku, Matfyzpress, Praha.

Z. Pawlas (2013): Pikomat MFF UK 2012-13: ročenka 28. ročníku, Matfyzpress, Praha.

Z. Pawlas (2012): Pikomat MFF UK 2011-12: ročenka 27. ročníku, Matfyzpress, Praha.

Z. Pawlas (2011): Pikomat MFF UK 2010-11: ročenka 26. ročníku, Matfyzpress, Praha.

Z. Pawlas a T. Toufar (2010): Pikomat MFF UK 2009-10: ročenka 25. ročníku, Matfyzpress, Praha.

O. Honzl a Z. Pawlas (2009): Pikomat MFF UK 2008-09: ročenka 24. ročníku, Matfyzpress, Praha.

Z. Pawlas a O. Honzl (2008): Pikomat MFF UK 2007-08: ročenka 23. ročníku, Matfyzpress, Praha.

Z. Pawlas (2007): Pikomat MFF UK 2006-07: ročenka 22. ročníku, Matfyzpress, Praha.

Z. Pawlas (2006): Pikomat MFF UK 2005-06: ročenka 21. ročníku, Matfyzpress, Praha.

J. Zhouf a kolektiv (2006): Matematické příběhy z korespondenčních seminářů, Prometheus, Praha.

Z. Pawlas a kolektiv (2005): Pikomat MFF UK 2004-05: ročenka 20. ročníku, Matfyzpress, Praha.

J. Foniok, Z. Pawlas (2004): Pikomat MFF UK 2003-04: ročenka 19. ročníku, Univerzita Karlova v Praze, Matematicko-fyzikální fakulta, Praha.

J. Foniok, Z. Pawlas (2003): Pikomat MFF UK 2002-03: ročenka 18. ročníku, Univerzita Karlova v Praze, Matematicko-fyzikální fakulta, Praha.

Z. Pawlas, J. Foniok (2002): Pikomat MFF UK 2001-02: ročenka 17. ročníku, Univerzita Karlova v Praze, Matematicko-fyzikální fakulta, Praha.

S. Kucková, Z. Pawlas, J. Foniok (2001): Pikomat MFF UK 2001-02: ročenka 16. ročníku, Univerzita Karlova v Praze, Matematicko-fyzikální fakulta, Praha.