The Fourth International Workshop "Applied Methods of Statistical Analysis. Nonparametric Methods in Cybernetics and System Analysis - AMSA'2017" 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 2017, the workshop will take place in the hotel "Grenada" located near one of the most beautiful Russian natural parks Stolby.
Within the framework of AMSA'2017, the XVI 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 Fourth International Workshop "Applied Methods of Statistical Analysis. Nonparametric Methods in Cybernetics and System Analysis" – AMSA'2017 was funded by RFBR according to the research project №17-01-20474 and was supported by the Russian Ministry of Education and Science (project 1.1009.2017/4.6).