Homepage of Natalia Markovich

 

Addresses:

Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

Tel: +007-495-3348820, Fax: +007-495-3349331

Email: markovic@ipu.rssi.ru,nat.markovich@gmail.com

Mail address: V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Profsoyusnaya str., 65, 117997 Moscow, Russia

Function: DrSc., Main Scientist

  • Resume:
  • I am working as a main scientist in the RAS. My research interests are associated with nonparametric statistics, density estimation techniques, statistic of extremal events, stochastic processes, multivariate analysis.
  • Research
  • CV

Teaching Experience

is prepared in the frame of the EU research project Euro-NGI "Design and Engineering of the Next Generation Internet Towards convergent multi- service networks".

Book

Some Recent Papers

Statistic of extremal events:

  • Maxima and sums of non-stationary random length sequences, 2020 Extremes DOI: 10.1007/s10687-020-00372-5 (with  Igor Rodionov),
  • Clusters of extremes: modeling and examples, 2017 Extremes DOI:10.1007/s10687-017-0285-5
  • Erratum to: modeling clusters of extreme values, Extremes,  2016, 19(1), pp. 139--142
  • Modeling clusters of extreme values, Extremes, 2014, Volume 17, Issue 1, pp 97-125
  • Clustering and Hitting Times of Threshold Exceedances and Applications, Int. J. Data Analysis Techniques and Strategies, Vol. 9, No. 4, 331- 347. 2017

Extremes in social networks:

  •  Distribution and Dependence of Extremes in Network Sampling Processes,  Computational Social Networks, 2:12, p. 1-21,  doi:10.1186/s40649-015-0018-3 2015 with Avrachenkov K.,   Sreedharan J.K.
  • Extremes control of complex systems with applications to social networks, 15th IFAC/IEEE/IFIP/IFORS Symposium on Information Control Problems in Manufacturing INCOM 2015, Ottawa, Canada May 11-13, Volume 48, Issue 3, Edited by Alexandre Dolgui, Jurek Sasiadek and Marek Zaremba, pp 1296-1301 2015 doi:10.1016/j.ifacol.2015.06.264

Extremes in telecommunication networks:

  • A cluster caching rule in next generation networks. Proceedings of the 18th international scientific conference Distributed computer and communication networks: control, computation, communications (DCCN-2015) p. 127-135 Moscow 2015
  •  Modeling and analysis of caching rules based on the popularity of objects. Proceedings of the IEEE 19th international scientific conference Distributed computer and communication networks: control, computation, communications (DCCN-2016) Moscow November, pp. 47--56 with Khrenov V., Krieger U.R.,

Estimation of heavy-tailed probability density function:

  • Estimation of heavy-tailed probability density function with application to Web data. Computational Statistics, 2004, 4., (ps) with R.E.Maiboroda (ps)
  • Nonparametric Estimation of Heavy-Tailed Density by the Discrepancy Method, Springer International Publishing Switzerland, Ricardo Cao, Gonzalez Manteiga, Wenceslao, Romo, Juan (Eds.), Nonparametric Statistics, Springer Proceedings in Mathematics \& Statistics, Vol. 175, pp 103-116, 2016 ISBN 978-3-319-41581-9

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    Estimation of extreme value index:

    • Modification of Moment-Based Tail Index Estimator: Sums versus Maxima, Springer International Publishing Switzerland, Patrice Bertail, Delphine Blanke, Pierre-Andre Cornillon, Eric Matzner-Lober (Eds.) Springer Proceedings in Mathematics and Statistics, Vol., pp. 85-102 2018 DOI: 10.1007/978-3-319-96941-1_10 ISBN 978-3-319-96941-1 with Vaiciulis M.
    • Class of semi-parametric estimators of heaviness of distribution tail and its applications. Automation and Remote Control, No. 10, 2019 with Vaiciulis M. 

    Estimation of renewal function:

  • Estimating Basic Characterestics of Arrival Processes in Telecommunication Network by Empirical Data. Telecommunication Systems 20:1,2,11-31, 2002. , with U.Krieger (ps)
  • (2004). Nonparametric renewal function estimation and smoothing by empirical data. 
    Preprint ETH, Zuerich.     (ps)
  • Nonparametric estimation of the renewal function by empirical data, 
    Stochastic Models, 22:2, 2006,with U.Krieger

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    High quantile estimation :

    • High quantile estimation for heavy-tailed distributions, Performance Evaluation, vol.62, Issues 1-4, October 2005.

     

    Statistics of telecommunication data:

  • Nonparametric estimation of long-tailed density functions and its application to the analysis of World Wide Web traffic. Performance Evaluation, 42,  pp. 205-222, 2000, with U.Krieger (ps)
  • Bivariate statistical analysis of TCP-flow sizes and durations, Annals of Operations Research, 2009, Vol.170, 1, 199-216. with Kilpi,J.
  •  Classification of Slice-Based VBR Video Traffic and Estimation of Link Loss by Exceedance. Computer Networks. 2009, Vol.53, 1137-1153. with Undheim U., Emstad P.
  • Statistical Analysis and Modeling of Skype VoIP Flows. Computer Communications (COMCOM), Vol.31, Supplement 1, 2010. with Krieger, U.R
  •  Quality Assessment of the  Packet Transport  of Peer-to-Peer Video Traffic in High-Speed Networks. Performance Evaluation, 70 (2013) 28–44
  •  Nonparametric Analysis of Extremes on Web Graphs: PageRank versus Max-Linear Model. Communications in Computer and Information Science (20th International Conference DCCN2017 Moscow), CCIS, Volume 700, pp.13-26, 2017 with Ryzhov M.S., Krieger U.R.
  • Statistical Clustering of a Random Network by Extremal Properties. Communications in Computer and Information Science (21th International Conference DCCN2017 Moscow), CCIS, Volume 919, pp.71-82, 2018 with Ryzhov M.S., Krieger U.R.
  • Cluster Modeling of Lindley Process with Application to Queuing. Proceedings of the IEEE 21th international scientific conference Distributed computer and communication networks: control, computation, communications (DCCN-2019) Moscow 23-28 September 2019, p. 53-58 with Razumchik R.V.

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