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
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Current rating (overall rating of articles)
0
TOP5 coauthors
Articles count: 139
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"

MODERN ECONOMETRIC METHODS  INTELLECTUAL TOOLS OF ENGINEERS, MANAGERS AND ECONOMISTS
01.00.00 Physicalmathematical sciences
DescriptionStatistical methods are widely used in domestic feasibility studies. However, for most managers, economists and engineers, they are exotic. This is because modern statistical methods are not taught in the universities. We discuss the situation, focusing on the statistical methods for economic and feasibility studies, ie, econometrics. In the world of science, econometrics has a rightful place. There are scientific journals in econometrics, Nobel Prizes in Economics are awarded to series of researches in econometrics. The situation in the field of scientific and practical work and especially the teaching of econometrics in Russia is disadvantaged. Often, individual particular constructions replace econometrics in general, such as those related to regression analysis. In econometrics we select three types of scientific and applied activities: development and study of methods of applied statistics, taking into account the specifics of economic data; development and study of econometric models, in accordance with the specific needs of economic science and practice; the use of econometric methods for statistical analysis of specific economic data. This article describes these three types of scientific and applied activities. We discuss the specificity of economic data. We show the importance of economic nonnumeric values. We discuss the statistics of interval data  scientific direction at the joint of metrology and statistics. We give the representation of the econometric models. Problems of application of econometric methods are considered as an example of inflation. We discuss the statistics and econometrics as the field of scientific and practical activities. We have examined econometric methods in practical and training activities

OPTIMAL PLAN OF INVENTORY CONTROL CANNOT BE FOUND BASED ON THE FORMULA OF THE SQUARE ROOT
01.00.00 Physicalmathematical sciences
DescriptionInventory management (in other words, logistics) is an integral part of the work of firms, companies and organizations. We are talking about stocks of raw materials, fuel, tools, components, semifinished products, finished products for industrial (or agricultural) firms, about stocks of goods to distribution centers, warehouses, shops, workplaces sellers, finally consumers. Stocks spent all the time and supplemented on various rules adopted in the firm. Optimization of these rules, ie, optimal inventory management, gives a big economic effect. The mathematical theory of inventory management, based on the models of movement of flows of goods, is an important area of economicmathematical research. The classical model of inventory management proposed in 1915 by F. Harris is one of the simplest and most illustrative examples of application of the mathematical apparatus for decisionmaking in the economic field. This model is commonly referred to as the Wilson model, because this model became known after the publication of R.G. Wilson in 1934. The formula of the optimum batch size (the socalled "the formula of the square root"), obtained in the Wilson model, is widely used on various stages of production and distribution, since this formula is practically useful for decisionmaking in the inventory management, in particular, for generating significant economic effect. However, contrary to popular belief, by means of this formula it is impossible to calculate the optimal batch size (although it is a necessary step on the path of its finding). In strict economicmathematical analysis of Wilson model, conducted in the article, it is shown that the formula of square root does not give the optimal batch size. We have given the algorithm for calculating the optimal batch size. It has been found that the formula of the square root gives asymptotically optimal plan. We have studied the stability of the conclusions in the economicmathematical model and considered an example of the practical application of the classical model of inventory management

ECONOMETRICS FOR THE CONNROLLERS
01.00.00 Physicalmathematical sciences
DescriptionRequirements for the professional training of сontrollers include, in particular, the requirements for an intelligent tool that controllers must possess. One of such tools is the econometrics. Organization of training, in particular, preparation of curricula, programs, teaching materials and textbooks, involves discussion of the scope and content of the relevant discipline. We have given the description of the econometric tools of controlling, including the courses of "Econometrics1" and "Econometrics2", which the Department of the IBM2 "Economics and organization of production" is on the faculty "Engineering and Business Management" of Bauman Moscow State Technical University. We have discussed the external environment of econometrics and the necessary changes in it. For example, the course of "Probability Theory and Mathematical Statistics" is the basis for the study of econometrics. However, it has to be brought into line with modern requirements. In particular, it is necessary to consider such things as random elements with values in an arbitrary space, empirical and theoretical means in such spaces, to prove the laws of large numbers in general statements. Simultaneously with the specified extension course content is reasonable to exclude from the program methods based on those assumptions are not met in the concrete economic situations. In particular, we have to eliminate the onesample and twosample Student's t tests and replace them with the corresponding nonparametric tests. We do not need the "classical" and geometric probability, etc. We have given the importance of the problem of constructing integral indicators in various problems of econometrics; issues of analysis of the situation by means of a system of indicators are discussed in detail

ABOUT THE KEY PERFORMANCE INDICATORS OF SCIENTIFIC ACTIVITIES
DescriptionOf the many urgent problems of Science about Science, we consider methods for estimation of the effectiveness and quality of the scientific activities of the researcher, of the organization, of the magazine. Performance indicators of scientific activity are used as an important part in the estimation of higher education institutions, the innovative capacity of enterprises, etc. To estimate the effectiveness of scientific activity is natural to use intellectual tools which are wellestablished in other subject areas. This will include, in particular, the balanced scorecard, based on key performance indicators (hence the title of this article), as well as controlling, primarily controlling of research activities. There are two more developed and widely used tools for estimation the effectiveness of the scientific activity  the scientometric indicators and the expert estimators. Their critical analysis is the subject of this article. Different versions of manipulating of values of scientometric indicators in the Russian Federation, in our estimation, are still relatively rare. Perhaps this is due to the relatively short period of their use in the management of science. Since an indicator such as citation index (the number of citations of publications) of researcher, allows estimating its contribution to science, the use of this scientometric indicator for the management of science is justified. At the same time, the number of publications and especially hindex is not possible to objectively estimate the effectiveness of research activities, particularly in view of the properties of the real bibliometric databases. Expert procedures have several disadvantages. In this article we discuss the real effectiveness of expert procedures in the areas of their application, as conferring academic degrees and elections to the National Academy of Sciences (primarily in the Russian Academy of Sciences). The basic principles of expertise in these areas remain the same for the past 70 years. Based on an analysis of practice it is necessary to ascertain the lack of efficacy of expert estimators in these areas. Rationale to what has been said is given in the article

01.00.00 Physicalmathematical sciences
DescriptionAccording to the new paradigm of applied mathematical statistics one should prefer nonparametric methods and models. However, in applied statistics we currently use a variety of parametric models. The term "parametric" means that the probabilisticstatistical model is fully described by a finitedimensional vector of fixed dimension, and this dimension does not depend on the size of the sample. In parametric statistics the estimation problem is to estimate the unknown value (for statistician) of parameter by means of the best (in some sense) method. In the statistical problems of standardization and quality control we use a threeparameter family of gamma distributions. In this article, it is considered as an example of the parametric distribution family. We compare the methods for estimating the parameters. The method of moments is universal. However, the estimates obtained with the help of method of moments have optimal properties only in rare cases. Maximum likelihood estimation (MLE) belongs to the class of the best asymptotically normal estimates. In most cases, analytical solutions do not exist; therefore, to find MLE it is necessary to apply numerical methods. However, the use of numerical methods creates numerous problems. Convergence of iterative algorithms requires justification. In a number of examples of the analysis of real data, the likelihood function has many local maxima, and because of that natural iterative procedures do not converge. We suggest the use of onestep estimates (OSestimates). They have equally good asymptotic properties as the maximum likelihood estimators, under the same conditions of regularity that MLE. Onestep estimates are written in the form of explicit formulas. In this article it is proved that the onestep estimates are the best asymptotically normal estimates (under natural conditions). We have found OSestimates for the gamma distribution and given the results of calculations using data on operating time to limit state for incisors

MAIN PROBLEMS OF CONTROLLING OF THE QUALITY
DescriptionControlling of statistical methods to ensure product quality is the special case of controlling organizational and economic methods of management. Today, controlling in the practice of management of Russian companies is understood as "the system of informationanalytical and methodological support to achieve their goals." The controller is developing a decisionmaking rules, the head takes decisions on the basis of these rules. We proved the concept of "controlling of methods". Innovation in management is based, in particular, on the use of new adequate organizationaleconomic (as well as economicmathematical and statistical) methods. Controlling in this area  is the development and application procedures of compliance management used and newly developed (implemented) organizationaleconomic methods for the task. Thus, the methodology for controlling is of great practical value in any field in which the actions (operations) must be carried out in accordance with certain rules (regulations, standards, guidelines), as in any such area in which we need to use development and application procedures of compliance management used and the newly established (implemented) rules for solution of tasks assigned to the organization. In this article, we select a area of controlling as controlling quality, and we discuss its main issues. This is about controlling of organizationaleconomic methods to ensure product quality, especially about the statistical methods based on probability theory and mathematical statistics. We consider the analysis and synthesis of plans of statistical quality control, optimization options plans of statistical control, truncated plans. Are discussed the differences control plans provider and the consumer, the allocation of units formless (liquid, gas) products, the selection of a random sample of the statistical quality control of products, lower estimate of the required sample size. It is established, that is not always necessary quality control. Is given the theory of the basic paradox of statistical quality control. We discuss the development of statistical methods for quality control in our country. Is given the classification of statistical methods of quality management

ECONOMETRIC TOOLS OF CONTROLLING
01.00.00 Physicalmathematical sciences
DescriptionEconometrics is one of the most effective mathematical tools of controlling. The article deals with general problems of application of econometric methods in solving problems of controlling. Econometric methods  is primarily a statistical analysis of concrete economic data, of course, with the help of computers. In our country, they are still relatively little known, even though we have the most powerful scientific school in the foundations of econometrics  the probability theory. The article shows that to decide the problems of controlling is necessary to apply econometric methods. Classification of econometric tools can be carried out on various grounds: on methods, by type of data, in tasks, etc. Mass introduction of software products, including modern econometric analysis tools of concrete economic data can be regarded as one of the most effective ways to accelerate scientific and technological progress. The whole arsenal currently used econometric and statistical techniques (methods) can be divided into three streams: high econometric (statistical) technology; classical econometric (statistical) technology, low (inadequate, obsolete) econometric (statistical) technology. The main problem of modern econometrics is to ensure that the concrete econometric and statistical studies used only the first two types of technology. To get a broader representation of the use of econometric methods in the management of production organization we analyze basic textbook "Organization and planning of engineering production (production management)," prepared by the Department of "Economics and organization of production" of the Bauman Moscow State Technical University. It has more than 20 times using econometric methods and models that testify to the effectiveness of such a tool of manager as econometrics

NONPARAMETRIC KERNEL ESTIMATORS OF PROBABILITY DENSITY IN THE DISCRETE SPACES
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 has been started in our articles [3, 4]. This article is a direct continuation of these works [3, 4]. We will regularly use references to conditions and theorems of the articles [3, 4], in which introduced several types of nonparametric estimators of the probability density. We have studied linear estimators. In this article, we consider particular cases  kernel density estimates in discrete spaces. When estimating the density of the onedimensional random variable, kernel estimators become the ParzenRosenblatt estimators. Under different conditions, we prove the consistency and asymptotic normality of kernel density estimators. We have introduced the concept of "preferred rate differences" and are studied nuclear density estimators based on it. We have introduced and studied natural affinity measures which are used in the analysis of the asymptotic behavior of kernel density estimators. Kernel density estimates are considered for sequences of spaces with measures. We give the conditions under which the difference between the densities of probability distributions and of the mathematical expectations of their nuclear estimates uniformly tends to 0. Is established the uniform convergence of the variances. We find the conditions on the kernel functions, in which take place these theorems about uniform convergence. As examples, there are considered the spaces of fuzzy subsets of finite sets and the spaces of all subsets of finite sets. We give the condition to support the use of kernel density estimation in finite spaces. We discuss the counterexample of space of rankings in which the application of kernel density estimators can not be correct

THEORETICAL TOOLS OF STATISTICAL METHODS
01.00.00 Physicalmathematical sciences
DescriptionWe have considered the basic mathematical tools (theorems, methods) which are used regularly in the justification of new results in the field of statistical methods: rules of large numbers, central limit theorems, the necessary and sufficient conditions for the inheritance of convergence, the linearization method, the invariance principle