Applied Methods of Statistical Analysis


Statistical Computation and Simulation


18-20 September, 2019 

NSTU

About workshop

The Fifth International Workshop Applied Methods of Statistical Analysis. Statistical Computation and Simulation - AMSA'2019 will be focused on the following issues:

  • urgent problems in applied mathematical statistics;
  • the role of computational methods and simulation techniques in the development of applied mathematical statistics;
  • prospective research results aimed at the expansion of application area of statistical methods in the case of deviation from standard assumptions;
  • problems of practical application of statistical methods for data analysis.

The AMSA aims to bring together specialists interested in the development of statistical methods of data analysis and correct and efficient practical application of these methods. In 2019, the workshop will take place in the hotel "Rassvet".

Within the framework of AMSA'2019, the XVII International Symposium on Nonparametric Methods in Cybernetics and System Analysis will be held. The main topics of the Symposium:

  • nonparametric and robust statistics;
  • nonparametric adaptive and trained systems;
  • identification, modeling, classification and processing images;
  • simulation and organizational systems control;
  • applications in design and usage of computer systems of various purposes and automation systems.

The topics of AMSA include, but not limited to, the followings:

  • Nonparametric and robust statistical methods in cybernetics
  • Multidimensional stochastic processes modeling and identification
  • Control under incomplete information
  • Decision making
  • Monte Carlo method in problems of applied statistics
  • Lifetime data analysis
  • Statistical simulation of natural processes
  • Econometric methods and modeling
  • Applications of statistical methods

The organization of the Fifth International Workshop Applied Methods of Statistical Analysis. Statistical Computation and Simulation – AMSA'2019 is supported by the Russian Ministry of Education and Science (project 1.1009.2017/4.6).

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