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: 138
Сформировать список работ, опубликованных в Научном журнале КубГАУ

ESTIMATION OF INFLATION ON THE BASIS OF INDEPENDENT INFORMATION
DescriptionThis article is devoted to the investigations of our research team built for independent collection and examination the information about prices, ie to study the real inflation. The approach to measuring the rise in prices is based on selecting and fixing tool of economists and managers  the consumer basket which does not change during the time. On the basis of physiological consumption norms of the Institute of Nutrition (Russian Academy of medical Sciences) we made up the minimum consumer basket, ie we set annual consumption on food staples required to maintain normal functioning of the human body. In 19932015 we carried out an independent price collection. We obtained values of the consumer basket and inflation indices. We give the comparison with the data of official statistics. Our work is aimed at the elimination of Rosstat's monopoly in calculating the index of inflation, the minimum subsistence level and the real disposable income of the population. Using the same consumer basket makes it possible to compare the results of calculations for different time periods. That is why our works compare favorably to the approach of the official statistics. We have given a more detailed analysis of inflation in the XXI century. We have also briefly reviewed the use of inflation indices in the analysis of problems of households, organizations and production firms, as well as the country as a whole

Description
The basic ideas of the developed by us solidary information economy are analyzed (the original name  the nonformal informational economy of the future). Its use as the base of modern organizationaleconomic theory in exchange for the term of “economics” is proved. The 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. As the economic component of state ideology of Russia we offer solidary information economy. According to the solidary information economy the modern information technology and decision theory allow, based on the “open network society”, to build information and communication system designed to identify the needs of people and the organization of production in order to meet them. To implement this feature we must have political will of leadership of economic unit, aimed at transforming the management of this economic unit. In particular, as is already happening in all developed countries, the Russian state should become a major player in the economy

INTERCONNECTION LIMIT THEOREMS AND MONTECARLO METHOD
01.00.00 Physicalmathematical sciences
DescriptionThe purpose of mathematical statistics is development of methods for the data analysis intended to solve applied problems. Over time, approaches to the development of data analysis methods have changed. A hundred years ago, it was assumed, that the distributions of the data have a certain type, for example, they are normal distributions, and on that assumption they developed a statistical theory. The next stage, in the first place in theoretical studies there are limit theorems. By "small sample" we mean a sample, which can not be applied to conclusions based on the limit theorems. In each statistical problem there is a need to divide the final sample sizes into two classes  those for which you can apply the limit theorems, and those for which you can not do it because of the risk of incorrect conclusions. To solve this problem we often used the Monte Carlo method. More complex problems arise when studying the effect on the properties of statistical procedures for data analysis of various deviations from the original assumptions. To study such impact, we often used the Monte Carlo method as well. The basic (and not solved in a general way) problem of the study of the stability of the findings in the presence of deviations from the parametric families of distributions is the problem of choosing some distributions for using in modeling. We consider some examples of application of the Monte Carlo method, relating to the activities of our research team. We have also formulated basic unsolved problems

REAL AND NOMINAL SIGNIFICANCE LEVELS IN STATISTICAL HYPOTHESIS TESTING
01.00.00 Physicalmathematical sciences
DescriptionIn the statistical hypothesis testing, critical values often point to a priori fixed (nominal) significance levels. As such, typically researcher uses the values of three numbers 0.01, 0.05, 0.1, to which may be added a few levels: 0.001, 0.005, 0.02, and others. However, for the statistics with discrete distribution functions, which, in particular, include all nonparametric statistical tests, the real significance levels may be different from the nominal, differ at times. Under the real significance level we refer to the highest possible significance level of discrete statistics, not exceeding a given nominal significance level (ie, the transition to the next highest possible value corresponding discrete statistical significance level is greater than a predetermined nominal). In the article, we have discussed the difference between nominal and real significance levels on the example of nonparametric tests for the homogeneity of two independent samples. We have also studied twosample Wilcoxon test, the criterion of van der Waerden, Smirnov twosample twosided test, sign test, runs test (Wolfowitz) and calculated the real significance levels of the criteria for nominal significance level of 0.05. The study of the power of these statistical tests is accomplished by means of Monte Carlo method. The main conclusion: the use of nominal significance levels instead of real significance levels for discrete statistics is inadmissible for small sample sizes

PREDICTION METHODS FOR THE ROCKET AND SPACE INDUSTRY
01.00.00 Physicalmathematical sciences
DescriptionWe have allocated the basic sources of uncertainty in various industrial and economic situations. We have also considered the role and the tasks of forecasting in the management of industrial companies, particularly in the rocket and space industry. We have discussed the methods of organizational and economic forecasting  statistical, expert, combined, including foresight and given some suggestions for improving the forecasting and planning mechanisms for practical use when creating space systems

Description
In many areas  the economy, quality management, medicine, the ecology, in safety of flights and others  the problems of analysis, estimation and management of risks have much in common. Therefore, we consider it necessary to develop a general theory of risk. Approaches and methods of this theory will allow in the future solving problems of uniform risk management in specific subject areas. Based on the analysis of scientific publications and industry regulations it must be noted that private risk theories tend to become isolated within themselves, create their own internal standards and systems of regulations. Separately  for banking, separately  for safety, separately  for industrial accidents, etc. In order to construct a general theory of risk we analyze use of the term "risk" in various fields, consider the variety of types of risks, give the basic definitions in the field of analysis, estimation and management of risk. We discuss planetary risks (at Earth as a whole), global risks (at the level of one or more States), financial risks, commercial risks (risks at the level of the immediate environment of the company), and production (internal, operational) risks relating to the activities of individual enterprises (organizations), personal risks. Instruments of total risk theory allow us equally solve the basic problems of analysis, estimation and management of risk for all areas

SCIENCE AS THE OBJECT OF MANAGEMENT
DescriptionScience is considered as a branch of the national economy. We discuss the relationship of areas of human activity, applied science and fundamental science. As an example, the development of the fundamental theory of decisionmaking and expertise are considered in the implementation of applied researches in the aviation and rocketspace industry. Is emphasized that the major achievement in science  the novelty of the results. We discuss the problem of estimation the effectiveness of scientific activity, the advantages and disadvantages of estimates based on bibliometric databases and citation indices, we show the basic role of expert technologies. Is examined the role of globalization and patriotism in the development of science. Is substantiated the principal difference between acquiring knowledge and promote research results. We consider it necessary to conduct detailed studies into the science of science and development based on these sciencebased recommendations for the management of science

STATISTICAL ESTIMATION FOR THE GROUPED DATA
01.00.00 Physicalmathematical sciences
DescriptionThe probabilistic model of grouping data (including multidimensional data) is described. We have also generalized EulerMaclaurin’s formulas. With its help Sheppard’s corrections and corrections on grouping for correlation coefficient are received. We have found and studied asymptotical corrections on grouping data generally. Accuracy of approach has been estimated

COMPUTERSTATISTICAL METHODS: STATE AND PROSPECTS
01.00.00 Physicalmathematical sciences
DescriptionWe have analyzed the current state of the main computerstatistical methods, identified achievements and existing problems, outlined the prospects of further movement and formulated the problems to be solved. We have also discussed the Monte Carlo methods, pseudorandom numbers, simulation, bootstrap and resampling, the automated systemcognitive analysis. We have considered the applications of computer statistics in controlling and properties of statistical packages as the tools for researchers

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