Scientific Journal of KubSAU

Inventory 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, semi-finished 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 economic-mathematical 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 decision-making 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 so-called "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 decision-making 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 economic-mathematical 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 economic-mathematical model and considered an example of the practical application of the classical model of inventory management

Requirements 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 "Econometrics-1" and "Econometrics-2", which the Department of the IBM-2 "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 one-sample and two-sample 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

The 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 decision-making 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 super-powerful 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"

Statistical 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 non-numeric 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

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 organizational-economic 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 organizational-economic 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

Some 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

We 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

The statistics of objects of non-numerical nature (statistics of non-numerical objects, non-numerical data statistics, non-numeric statistics) is the area of mathematical statistics, devoted to the analysis methods of non-numeric data. Basis of applying the results of mathematical statistics are probabilistic-statistical models of real phenomena and processes, the most important (and often only) which are models for obtaining data. The simplest example of a model for obtaining data is the model of the sample as a set of independent identically distributed random variables. In this article we have considered the basic probabilistic models for obtaining non-numeric data. Namely, the models of dichotomous data, results of paired comparisons, binary relations, ranks, the objects of general nature. We have discussed the various options of probabilistic models and their practical use. For example, the basic probabilistic model of dichotomous data - Bernoulli vector (Lucian) i.e. final sequence of independent Bernoulli trials, for which the probabilities of success may be different. The mathematical tools of solutions of various statistical problems associated with the Bernoulli vectors are useful for the analysis of random tolerances; random sets with independent elements; in processing the results of independent pairwise comparisons; statistical methods for analyzing the accuracy and stability of technological processes; in the analysis and synthesis of statistical quality control plans (for dichotomous characteristics); the processing of marketing and sociological questionnaires (with closed questions like "yes" - "no"); the processing of socio-psychological and medical data, in particular, the responses to psychological tests such as MMPI (used in particular in the problems of human resource management), and analysis of topographic maps (used for the analysis and prediction of the affected areas for technological disasters, distributing corrosion, propagation environmentally harmful pollutants, various diseases (including myocardial infarction), in other situations), etc.

In practical use of methods of applied statistics we do not apply separate methods for describing data, estimation, testing hypotheses, but we must use deployed whole procedures - the so-called "statistical technology". The concept of "statistical technology" is similar to the concept of "technological process" in the theory and practice of organization of production. It is quite natural that some statistical technology can better meet the needs of the researcher (user, statistics) than others, some - are modern, and others - outdated, some properties are studied, and the others - no. It is important to stress that a qualified and efficient use of statistical methods - this is not one single statistical hypothesis testing and estimation of characteristics or parameters of a given distribution from fixed family. This kind of operations - only the individual building blocks that make up the statistical technology. The procedure of the statistical data analysis - is an information process, in other words, one or other information technology. Statistical information is subject to a variety of operations (series, parallel, or more complex schemes). In this article we discuss statistical technologies and the problem of "docking" algorithms. We introduce the concept of "high statistical technologies" and then we prove the necessity of their development and application. As the examples we have given the researches of Institute of high statistical technologies and econometrics of Bauman Moscow State Technical University. We have also considered a number of education problems in domain of high statistical technologies

In the USSR higher attestation Commission from 1975 to the collapse of the USSR was subordinated not to the Ministry of education and science, but to the Council of Ministers of the USSR directly. However, since then there is a steady trend of gradual reduction of the status of the Commission. Today it is not just included in the Ministry of education, it is just one of the units of one of its structures: the Rosobrnadzor. Reduced status of the HAC inevitably leads to a decline in the status and in the adequacy of scientific degrees assigned as well as scientific ranks. This process of devaluation of traditional academic degrees and titles assigned to the HAC, has reached the point when a few years ago there were abolished salary increments for them. Now, instead of that, every university and research institutes have developed their local, i.e. non-comparable with each other scientometric methods of evaluation of the results of scientific and teaching activities. Despite the diversity of these techniques, there is a common thing among all of them, which is the disproportionate role of the h-index. The value of the Hirsch index starts to play an important role in the protection, when considering competitive cases for positions, as well as in determining the monthly rewards for the results of scientific and teaching activities. By itself, this index is well founded, theoretically. However, in connection with the practice of its application in our conditions, in the collective consciousness of the scientific community there was a kind of mania, which the authors call the "Hirschmania". This mania is characterized by elevated unhealthy interest to the value of the Hirsch index, as well as incorrect manipulation of its value, i.e. inadequate artificial exaggeration of this value, as well as a number of negative consequences of that interest. In this study we have made an attempt to construct a quantitative measure for assessing the extent of improper manipulation of the value of the Hirsch index, and offered a science-based modification of the h-index, insensitive (resistant) to the manipulation. The article presents a technique for all the numerical calculations, which is simple enough for any author to use