Research of Department "Economic Cybernetics and Information Technologies"
The Department is actively working towards the introduction of scientific developments in the national economy. The general direction of scientific work of the department can be described as the use of cybernetic methods of statistical analysis, simulation and mathematical programming in developing methods for improving the economic situation of enterprises.
1) ¹ state registration topic 0104U002027 "Economic-mathematical studies and information support innovative ways of regional development" Supervisor Kochura Eugene V., the perpetrators: Pistunov Igor.
2) ¹ state registration topic 0106U008092 "Automation of rudopidhotovky and ore dressing on the basis of the principle of the pilot system" supervisor Kochura Eugene V., the perpetrators: Pistunov Igor.
3) ¹ state registration 0106U008093 "Mathematical modeling and optimization of organization and management of mining and metallurgical enterprises of Ukraine" Supervisor Kochura Eugene V., the perpetrators: Pistunov Igor.
4) ¹ state registration 0109U001359 "Development and application of methods of economic-mathematical modeling and optimization in the economic activity of enterprises" Supervisor Pistunov Igor responsible agent: Elena Churikanova.
5) ¹ state registration topic 0110U001281 "Increasing the economic efficiency of mining and metallurgical enterprises on the basis of economic-mathematical methods" Supervisor Pistunov Igor responsible agent: Elena Churikanova.
In New York publishing house Springer was published scientific work of professor Korhin A.S. Regression Analysis Under A Priori Parameter Restrictions.
ÀBOUT THIS BOOKConstruction of various models of objects under uncertainty is one of the most important problems in modern decision making theory. Regression models are some of the most prevalent tools for modeling under uncertainty and are widely applied in different branches of science such as in industrial research, agriculture, medicine, and business and economics. Regression Analysis Under A Priori Parameter Restrictions will be of interest to a broad spectrum of readers in applied mathematics, mathematical statistics, identification theory, systems analysis, econometrics, finance, optimization, and other scientific disciplines. Requiring a background in algebra, probability theory, mathematical statistics, and mathematical programming, this work may also be a useful supplement for advanced graduate courses in estimation theory, regression analysis, mathematical statistics, econometrics, mathematical programming and optimal control, and stochastic optimization.
The material contained in this monograph successfully combines interesting theoretical results with methods and algorithms for solving practical problems. It focuses on the construction of regression models with linear and non-linear constraint inequalities and is the first book in which the theoretical results lying in the background of construction and studying regression models with inequality constraints on parameters are presented systematically and solidly.
Problems are described and studied in a clear, precise, and rigorous method and include: calculation of estimates for regression parameters, determination of their asymptotic properties and accuracy of estimation, point and interval prediction by the regression, parameters of which are estimated under inequality constraints. The authors’ approach lends itself to numerous applications in various practical problems, several of which are discussed in detail.
Content Level » Graduate
Keywords » Computational Modeling - Inequality Restrictions - Predictive Regression - Statistical Regression