Homepage of Natalia Markovich



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".


Some Recent Papers

Statistic of extremal events:

Markovich N.M. Clusters of extremes: modeling and examples, 2017 Extremes DOI:10.1007/s10687-017-0285-5

Markovich N.M. Modeling clusters of extreme values, Extremes, March 2014, Volume 17, Issue 1, pp 97-125

Markovich N.M. Clustering and Hitting Times of Threshold Exceedances and Applications, 2016 (Forthcoming paper in IJDATS)

Extremes in social networks:

Avrachenkov K.,  Markovich N. M.,  Sreedharan J.K. 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

Markovich N.M. 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:

Markovich N.M. 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

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)
  • 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.
  • Nonparametric estimation of the renewal function by empirical data, 
    Stochastic Models, 22:2, 2006,with U.Krieger
    • 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, with U.Krieger (ps)
    • Markovich N.M., Kilpi,J., Bivariate statistical analysis of TCP-flow sizes and durations, Annals of Operations Research, 2009, Vol.170, 1, 199-216.
    • Markovich N.M., Undheim U., Emstad P., Classification of Slice-Based VBR Video Traffic and Estimation of Link Loss by Exceedance. Computer Networks. 2009, Vol.53, 1137-1153.
    • Markovich N.M., Krieger, U.R., Statistical Analysis and Modeling of Skype VoIP Flows. Computer Communications (COMCOM), Vol.31, Supplement 1, 2010.
    •  Quality Assessment of the  Packet Transport  of Peer-to-Peer Video Traffic in High-Speed Networks. Performance Evaluation, 70 (2013) 28–44