Bauman Moscow State Technical University
Author list of organization
List of articles written by the authors of the organization
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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 decision-making and expertise are considered in the implementation of applied researches in the aviation and rocket-space 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 science-based recommendations for the management of science
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01.00.00 Physical-mathematical sciences
DescriptionAdequate and effective assessment of the efficiency, effectiveness and the quality of scientific activities of specific scientists and research teams is crucial for any information society and a society based on knowledge. The solution to this problem is the subject of scientometrics and its purpose. The current stage of development scientometrics differs greatly from his previous appearance in the open as well as paid on-line access to huge amount of detailed data on a large number of indicators on individual authors and on scientific organizations and universities. The world has well-known bibliographic databases: Web of Science, Scopus, Astrophysics Data System, PubMed, MathSciNet, zbMATH, Chemical Abstracts, Springer, Agris, or GeoRef. In Russia, it is primarily the Russian scientific citing index (RSCI). RSCI is a national information-analytical system, accumulating more than 9 million publications of Russian scientists, as well as the information about citation of these publications from more than 6,000 Russian journals. There is too much information; it is so-called "Big data". But the problem is how to make sense of these large data, more precisely, to identify the meaning of scientometric indicators) and thus to convert them into great information ("great information"), and then apply this information to achieve the objective of scientometrics, i.e. to transform it into a lot of knowledge ("great knowledge") about the specific scientists and research teams. The solution to this problem is creating a "Scientific smart metering system" based on the use of the automated system-cognitive analysis and its software tools – an intellectual system called "Eidos". The article provides a numerical example of the creation and application of Scientometric intelligent measurement system based on a small amount of real scientific data that are publicly available using free on-line access to the RSCI
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NONPARAMETRIC AND APPLIED STATISTICS IN OUR COUNTRY
01.00.00 Physical-mathematical sciences
DescriptionWe continue the series of articles about the history of statistics. We discuss the development of nonparametric and applied statistics in our country in 1930 - 1980 years. We have presented the studies of the great statisticians of the twentieth century, such as N.V. Smirnov, L.N. Bolshev, V.V. Nalimov. American statistics show Russian debate about applied statistics. We have briefly listed the process of creation of the All-Union Statistical Association (1990) and its further developments
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01.00.00 Physical-mathematical sciences
DescriptionIn the article we have considered A. N. Kolmogorov and N. V. Smirnov papers dedicated to one-sided and two-sided goodness-of-fit and homogeneity tests. It has been shown that the term "Kolmogorov - Smirnov test" used incorrectly. We have also given the recommendations on use of the terms "Kolmogorov test", "Smirnov test", "test of Kolmogorov-Smirnov type" and discussed omega-square test (Cramer-von Mises–Smirnov test). Typical errors in the application of these criterions have been considered, in particular to test for normality of the distribution of measurement results
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NON-PARAMETRIC CYCLES ESTIMATORS
01.00.00 Physical-mathematical sciences
DescriptionIn many applications, we study the time series (or a random process), which is the sum of the periodic deterministic function of time and random errors that distort the periodic signal. It is required to estimate the length of the period and the periodic component. It does not assume that the periodic function is included in any parameter family of functions, such as finite sums of sines and cosines. It is obvious that the assumption of occurrence of a periodic function in parametric family does not meet the characteristics of the real world, ie, is conditional, internal mathematical (look for the keys under the lamp because there is a light, not in the bush, where lost, because there are dark). For similar reasons, it is impossible to assume that the distribution function of the random errors is included in any parameter family of distributions. In accordance with the new paradigm of mathematical statistics in this article we studied the problem of nonparametric estimation (minimum) length of the period and the periodic component of the signal. On the basis of natural variation and scope of indicators is suggested a new class of nonparametric estimators of the length of the period and the periodic component in the time series. Based on the general results of statistics of objects of non-numeric nature we proved the consistency of these estimates. From the practical point of view it is necessary to minimize the numerical (one parameter - ability length of period of time) one or more of the 66 functionals, described in the article
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NONPARAMETRIC KERNEL ESTIMATORS OF PROBABILITY DENSITY IN THE DISCRETE SPACES
01.00.00 Physical-mathematical sciences
DescriptionSome estimators of the probability density function in spaces of arbitrary nature are used for various tasks in statistics of non-numerical 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 one-dimensional random variable, kernel estimators become the Parzen-Rosenblatt 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
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NONPARAMETRIC ESTIMATION OF CHARACTERISTICS OF PROBABILITY DISTRIBUTIONS
01.00.00 Physical-mathematical sciences
DescriptionThe article is devoted to the nonparametric point and interval estimation of the characteristics of the probabilistic distribution (the expectation, median, variance, standard deviation, variation coefficient) of the sample results. Sample values are regarded as the implementation of independent and identically distributed random variables with an arbitrary distribution function having the desired number of moments. Nonparametric analysis procedures are compared with the parametric procedures, based on the assumption that the sample values have a normal distribution. Point estimators are constructed in the obvious way - using sample analogs of the theoretical characteristics. Interval estimators are based on asymptotic normality of sample moments and functions from them. Nonparametric asymptotic confidence intervals are obtained through the use of special output technology of the asymptotic relations of Applied Statistics. In the first step this technology uses the multidimensional central limit theorem, applied to the sums of vectors whose coordinates are the degrees of initial random variables. The second step is the conversion limit multivariate normal vector to obtain the interest of researcher vector. At the same considerations we have used linearization and discarded infinitesimal quantities. The third step - a rigorous justification of the results on the asymptotic standard for mathematical and statistical reasoning level. It is usually necessary to use the necessary and sufficient conditions for the inheritance of convergence. This article contains 10 numerical examples. Initial data - information about an operating time of 50 cutting tools to the limit state. Using the methods developed on the assumption of normal distribution, it can lead to noticeably distorted conclusions in a situation where the normality hypothesis failed. Practical recommendations are: for the analysis of real data we should use nonparametric confidence limits
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NEW AREA OF CONTROLLING –CONTROLLING OF ORGANIZATIONAL-ECONOMIC METHODS
DescriptionWe introduce the concept of "controlling organizational-economic methods". We define the terms in the sequence "the problem - the model - the method - the conditions of applicability". We have described the basic organizational-economic model of industrial firm; by means of this model we have discussed the problems of development of modern organizational-economic methods. We have demonstrated the relevance of the theory and methodology of organizational-economic modeling. For example, we consider the application of statistical methods at various stages of the life cycle of the product, the problem of internal risks in an industrial firm and accounting for inflation in the analysis of activities of the organization
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NEW PARADIGM OF ANALYSIS OF STATISTICAL AND EXPERT DATA IN PROBLEMS OF ECONOMICS AND MANAGEMENT
DescriptionThe article is devoted to the methods of analysis of statistical and expert data in problems of economics and management that are discussed in the framework of scientific specialization "Mathematical methods of economy", including organizational-economic and economic-mathematical modeling, econometrics and statistics, as well as economic aspects of decision theory, systems analysis, cybernetics, operations research. The main provisions of the new paradigm of this scientific and practical field are developed by the author of this article in the 1980s during the creation of the All-Union Statistical Association. The new paradigm is compared with the old (corresponding to the middle of XX century). Is summarized monographs, textbooks and manuals prepared under the leadership of the author of this paper in the XXI century according to the new paradigm
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01.00.00 Physical-mathematical sciences
DescriptionThe relationship of Mathematical Statistics (wider - Mathematical methods of research) and history is multifaceted. In our opinion, the history of mathematical statistics is an integral part of this mathematical discipline. We have given a review of our works on the history of statistical methods. The role of mathematical statistics for the history is very important. In this article, we restrict ourselves to the questions of chronology. For centuries, the chronology is considered as a part of applied mathematics. The main problem is that the whole "common" concept of the Russian and the World history as a whole presented in textbooks was faked by the opponents of Russia after the collapse of the global Empire (Russian kingdom) in the early 17th century - 400 years ago. The stories about historical events are the information weapon. It was used by the new rulers to suppress the resistance of the vanquished. A new mathematical and statistical chronology of general and Russian history, which was built by a scientific team led by Academician Fomenko, has been helpful for the discussion about the current economic and political problems of relations between Russia and the West in the XXI century. In our opinion, the new chronology of the World and Russian history should be one of the foundations of state-patriotic ideology and deriving practical solutions. The purpose of this article is to give the initial idea of the new chronology from this point of view