name
Orlov Alexander Ivanovich
Scholastic degree
•
•
•
Academic rank
professor
Honorary rank
—
Organization, job position
• Bauman Moscow State Technical University
Research interests
статистические методы, организационноэкономическое моделирование. Разработал новую область прикладной статистики — статистику объектов нечисловой природы
Web site url
—
Current rating (overall rating of articles)
0
TOP5 coauthors
Articles count: 145
Сформировать список работ, опубликованных в Научном журнале КубГАУ

CONSEQUENCES OF DECISIONS FOR SCIENCETECHNOLOGY AND ECONOMIC DEVELOPMENT
DescriptionThe real facts presented in this article, demonstrate the great importance in today's world of strategic management, methods of analyses of innovations and investments and the role of the theory of decisionmaking in these economic disciplines. We have given the retrospective analysis of the development of nuclear physics research. For the development of fundamental and applied science in the second half of the twentieth century, we had a very great importance of the two events: the decision of US President Roosevelt to deploy nuclear program (adopted in response to a letter from Einstein) and the coincidence in time between the completion of the construction of nuclear bomb and the end of World War II. The nuclear bombing of Hiroshima and Nagasaki has determined the developments in science and technology for the entire second half of the twentieth century. For the first time in the entire history of the world the leaders of the leading countries clearly seen that fundamental research can bring great practical benefit (from the point of view of the leaders of countries). Namely, they can give the brand new superpowerful weapon. The consequence was a broad organizational and financial support of fundamental and deriving from them applied research. Is analyzed the influence of fundamental and applied research on the development and effective use of new technology and technical progress. We consider the development of mathematical methods of research and information technology, in particular, the myth of "artificial intelligence"

LIMIT THEORY OF NONPARAMETRIC STATISTICS
01.00.00 Physicalmathematical sciences
DescriptionWe have studied the asymptotic behavior of a broad class of nonparametric statistics, which includes statistics of omegasquare type and KolmogorovSmirnov type. Limit theorems have been proved. We have also developed the method of approximation with step functions. With the help of this method we have obtained a number of necessary and sufficient conditions

THE LIMIT THEORY OF THE SOLUTIONS OF EXTREMAL STATISTICAL PROBLEMS
01.00.00 Physicalmathematical sciences
DescriptionMany procedures of applied mathematical statistics are based on the solution of extreme problems. As examples it is enough to name methods of least squares, maximum likelihood, minimal contrast, main components. In accordance with the new paradigm of applied mathematical statistics, the central part of this scientific and practical discipline is the statistics of nonnumerical data (it is also called the statistics of objects of nonnumerical nature or nonnumeric statistics) in which the empirical and theoretical averages are determined by solving extreme problems. As shown in this paper, the laws of large numbers are valid, according to which empirical averages approach the theoretical ones with increasing sample size. Of great importance are limit theorems describing the asymptotic behavior of solutions of extremal statistical problems. For example, in the method of least squares, selective estimates of the parameters of the dependence approach the theoretical values, the maximum likelihood estimates tend to the estimated parameters, etc. It is quite natural to seek to study the asymptotic behavior of solutions of extremal statistical problems in the general case. The corresponding results can be used in various special cases. This is the theoretical and practical use of the limiting results obtained under the weakest assumptions. The present article is devoted to a series of limit theorems concerning the asymptotics of solutions of extremal statistical problems in the most general formulations. Along with the results of probability theory, the apparatus of general topology is used. The main differences between the results of this article and numerous studies on related topics are: we consider spaces of a general nature; the behavior of solutions is studied for extremal statistical problems of general form; it is possible to weaken ordinary requirements of bicompactness type by introducing conditions of the type of asymptotic uniform divisibility

LIMIT THEOREMS IN STATISTICAL CONTROL
01.00.00 Physicalmathematical sciences
DescriptionThe article analyzes the development of the theory of statistical control (from the XVIII century to the present). Prof. M.V. Ostrogradskii (1846) clearly describes the practical needs (ie, arising from the quality assurance of large quantities of bags of flour or pieces of cloth), to meet whom he spent his research. At the same time Simpson was among the ideas of probability theory XVIII century. Therefore prof. M.V. Ostrogradskii may be regarded as the founder of the theory of statistical process control (not only in our country but all over the world). Limit theorems of probability theory and mathematical statistics have provided a number of asymptotic results in problems of statistical quality control, offer based on these best practices. However, we must find out how much interest among specialists characteristics are different from limit for finite sample sizes. Such research for the synthesis algorithm control plan on the basis of the limit average output level of defects is made in this article, and for the synthesis algorithm control plan on the basis of the acceptance and the rejection levels of defects  not yet (clarification of the conditions of applicability of this algorithm  unsolved problem of applied mathematics). We have briefly reviewed the development of our researches on the statistical control. Control units can be not only some units of production, but also documents (with internal and external audit), and standard units of air, water and soil in the environmental monitoring. One of the achievements can be regarded as the transfer of statistical control of production for environmental monitoring

LIMIT THEOREMS FOR KERNEL DENSITY ESTIMATORS IN SPACES OF ARBITRARY NATURE
01.00.00 Physicalmathematical sciences
DescriptionSome estimators of the probability density function in spaces of arbitrary nature are used for various tasks in statistics of nonnumerical data. Systematic exposition of the theory of such estimators had a start in our work [2]. This article is a direct continuation of the article [2]. We will regularly use references to conditions and theorems of the article [2], in which we introduced several types of nonparametric estimators of the probability density. We studied more linear estimators. In this article we consider particular cases  kernel density estimates in spaces of arbitrary nature. When estimating the density of the onedimensional random variable, kernel estimators become the ParzenRosenblatt estimators. Asymptotic behavior of kernel density estimators in the general case of an arbitrary nature spaces are devoted to Theorem 1  8. Under different conditions we prove the consistency and asymptotic normality of kernel density estimators. We have studied uniform convergence. We have introduced the concept of "preferred rate differences" and studied nuclear density estimators based on it. We have also introduced and studied natural affinity measures which are used in the analysis of the asymptotic behavior of kernel density estimators. We have found the asymptotic behavior of dispersions of kernel density estimators and considered the examples including kernel density estimators in finitedimensional spaces and in the space of squareintegrable functions

APPLIED STATISTICS – THE STATE AND THE PROSPECTS
01.00.00 Physicalmathematical sciences
DescriptionApplied Statistics  the science of how to analyze the statistical data. As an independent scientificpractical area it develops very quickly. It includes numerous widely and deeply developed scientific directions. Those who use the applied statistics and other statistical methods, usually focused on specific areas of study, ie, are not specialists in applied statistics. Therefore, it is useful to make a critical analysis of the current state of applied statistics and discuss trends in the development of statistical methods. Most of the practical importance of applied statistics justifies the usefulness of the work on the development of its methodology, in which the field of scientific and applied activities would be considered as a whole. We have given some brief information about the history of applied statistics. Based on Scientometrics of Applied Statistics we state that each expert has only a small part of accumulated knowledge in this area. We discuss five topical areas in which modern applied statistics develops, ie five "points of growth": nonparametric, robustness, bootstrap, statistics of interval data, and statistics of nonnumerical data. We discuss some details of the basic ideas of a nonnumerical statistics. In the last more than 60 years in Russia, there has been a huge gap between official statistics and the scientific community of experts on statistical methods

08.00.13 Mathematical and instrumental methods of Economics
DescriptionThe instrumental methods of economics include the Monte Carlo method (statistical simulations method). It is widely used in the development, study and application of mathematical research methods in econometrics, applied statistics, organizational and economic modeling, in the development and making management decisions, in the basis of simulation modeling. The new paradigm of mathematical research methods developed by us is based on the use of the Monte Carlo method. In mathematical statistics, limit theorems on the asymptotic behavior of the considered random values were obtained for many methods of data analysis with an unlimited increase in sample volumes. The next step is to study the properties of these random values for finite sample sizes. For such a study, the MonteCarlo method is used. In this article, we use this method to study the properties of statistical criteria for testing the homogeneity of two independent samples. We considered the most used in the analysis of real data criteria  CramerWelch, which coincides with the equality of the sample sizes with Student's criterion; Lord, Wilcoxon (MannWhitney), Wolfowitz, Van der Waerden, Smirnov, type omegasquare (LehmannRosenblatt). The Monte Carlo method allows us to estimate the rates of convergence of distributions of criteria statistics to the limits, to compare the properties of the criteria for finite sample sizes. To use the Monte Carlo method, it is necessary to select the distribution functions of the elements of the two samples. For this purpose, normal and Weibull – Gnedenko distributions are used. The recommendation was received: to test the hypothesis of coincidence of distribution functions of two samples, it is advisable to use the LehmannRosenblatt (type omegasquare) test. If there is reason to assume that the distributions differ mainly by the shift, then the Wilcoxon test and Van der Waerden criteria can also be used. However, even in this case, the omegasquare type test may be more powerful. In the general case, besides the LehmannRosenblatt criterion, the use of the Smirnov criterion is permissible, although for this criterion the real level of significance may differ from the nominal level of significance. We sstudied the frequency of discrepancies of statistical findings on different criteria

THE PROBLEMS OF IMPLEMENTATION OF MATHEMATICAL AND TOOL METHODS OF CONTROLLING
01.00.00 Physicalmathematical sciences
DescriptionStatistical methods are based on the developed theory and demonstrated its usefulness in the sectors of the economy. However, the analysis of the situation in the application of statistical methods shows obvious distress, in which accumulated in our country's scientific potential is not used to the full. As practice shows, it is not enough to develop promising modern theorybased effective mathematical and instrumental methods of controlling. For using such methods in mass, it is necessary that they would be implemented. Management of innovations, i.e. innovation management, quite rightly is currently one of the most debated sections of the economy and the organization of production, of the entire economic science in general. However, the implementation of applied statistics and other statistical methods, more generally, mathematical and instrumental methods of controlling, has its own specifics. It is considered in the article. We have highlighted the developmental vulnerabilities  low scientific level of many individuals applying statistical methods, the lack of organizational structure of applied statistics as a field of applied activities and others. We regret to note that the very idea of the need to establish requirements for the methods of data analysis and project formulations such requirements remained outside the attention of those professionals who need them and were addressed. We have no adequate system of guidance for documents on concrete statistical methods performed on modern scientific level. According to the author, the desired future of applied statistics is reorganization according to the model of Metrology. We have analyzed the application of statistical methods as a specialty. The analysis of state standards on statistical methods and the causes of them blunders are given. We have discussed the status of documents for statistical methods for standardization and quality control. We discuss a new system of "Six Sigma" for implementation advanced mathematical and instrumental methods of controlling

Description
The basic ideas of nonformal informational economy of the future (NIEF) are analyzed. Its use as the base organizationaleconomic theory in exchange «economics» is proved. Core of researches in the field of the NIEF is forecasting of development of the future society and its economy, working out of organizationaleconomic methods and models, necessary for the future and intended for increase of efficiency of managerial processes. The economy is a science how to make, instead of, how to divide profit. The basic kernel of the modern economic theory is an engineering economy

MANAGEMENT PROBLEMS IN SMALL PRODUCTION COMPANIES AT EARLY LIFECYCLE STAGES
DescriptionIn 1970 in the journal publications of "Forbes" and "Business week" the term of "startup" appeared, which later became popular in the scientific and business literature. Startups are the organizations, which create a new product or service under conditions of high uncertainty. In the last 2530 years, due to Russia's transition from a planned economy to the mixed, many researchers and practitioners in the field of management, economics and entrepreneurship are concerned of some questions of small business, including production. It is particularly acute problem of deaths of Russian small businesses: only three out of a hundred small businesses manage to survive for more than 3 years. In addition, one of the main reasons, why we have such statistics, is management deficiencies and administrative errors, which are studied in this article. We are primarily interested in small manufacturing plants and problems of development in the early stages of the life cycle. In the literature, it has been given just little attention. A small production company is a company associated with the production organization or incorporation of the product / technology in the production process. We regard the small production companies at an early stage of development, working in the field of mechanical engineering, instrumentation, energy, telecommunications, robotics, materials production. In this work, we analyze the first foreign and then domestic research on small business, discuss the problems of management of small industrial enterprises in the early stages of the life cycle (based on the results of our questionnaire studies) and as an example, consider the story of a startup  AllUnion Center of statistical methods and Informatics of Central Board of the AllUnion economic society (now  Institute of high statistical technologies and econometrics of Bauman Moscow State Technical University)