Name
Orlov Alexander Ivanovich
Scholastic degree
•
•
•
Academic rank
professor
Honorary rank
—
Organization, job position
Bauman Moscow State Technical University
Web site url
—
Articles count: 155
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 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 one-dimensional random variable, kernel estimators become the Parzen-Rosenblatt 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 finite-dimensional spaces and in the space of square-integrable functions
According to the new paradigm of applied mathematical statistics one should prefer non-parametric methods and models. However, in applied statistics we currently use a variety of parametric models. The term "parametric" means that the probabilistic-statistical model is fully described by a finite-dimensional 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 three-parameter 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 one-step estimates (OS-estimates). They have equally good asymptotic properties as the maximum likelihood estimators, under the same conditions of regularity that MLE. One-step estimates are written in the form of explicit formulas. In this article it is proved that the one-step estimates are the best asymptotically normal estimates (under natural conditions). We have found OS-estimates for the gamma distribution and given the results of calculations using data on operating time to limit state for incisors
Estimates of the errors of the characteristics of financial flows of investment projects are needed to make adequate management decisions, particularly in the rocket and the space industry. Organizational-economic approaches to the estimations of the feasibility of innovation-investment projects to create rocket and space technologies require intensive use of numerical characteristics of the financial flows of long-term projects of this type. In organizational-economic support for control problems in the aerospace industry we must provide the need to obtain the estimates of the errors of the characteristics of financial flows. Such estimates are an integral part of the organizational-economic support of innovation activity in the aerospace industry. They can be compared with the predictions interval, i.e. confidence estimation of predictive values. Half the length of the confidence interval is the prediction error estimate. In this article we give the new method for estimating the errors of the main characteristics of the investment projects. We focus on the net present value called NPV. Our method of estimation of errors is based on the results of statistics interval data, which is an integral part of the system fuzzy interval mathematics. We construct asymptotic theory which corresponds to small deviations of discount coefficients. The error of NPV has been found as the asymptotic notna. With up to infinitesimals of higher orders the error of NPV is a linear function of the maximum possible error of discount coefficients
Improvement of the organizational structures can increase the efficiency of enterprises. Controlling of personnel in companies such as "Research Institute" is a tool to support personnel decisions; it contributes to the strategic goals and tactical objectives. This article describes the main types of organizational structures, their properties, sociometric research as a tool for management, the stages of implementation of model of controlling of personnel in human resource management system for companies such as "Research Institute". Controlling of personnel is in regulation of HR processes, benchmarking, monitoring the implementation of the goals, taking into account the costs of implementing improved management systems, etc. It aims to determine the quality, efficiency and optimality of specific mechanisms, technologies and methods for the implementation of the HR function. Objectively, the volume of realization of the HR function depends on the presence of a certain quantities of material, labor, financial and other resources, on the objectives of the enterprise at different stages of the life cycle, as well as the number and qualifications of personnel. The quality of realization of the HR function depends on the level of its top-management's understanding of the importance of human resource management in the enterprise, as well as of the skill level of middle management. Controlling of HR function allows us to create an information base for effective management decisions that can help us to optimize the system of personnel management in the circumstances of the market environment, which is a necessary basis for the successful development of enterprises working in the field of high technology products and services
Currently, the majority of scientific, technical and economic studies use statistical methods developed mainly in the first third of the XX century. They constitute the content of common textbooks. However, mathematical statistics are rapidly developing in the next 60 years. In some situations there is a need of the transition from classical to modern methods. As an example, we discuss the problem of testing the homogeneity of two independent samples. We have considered the conditions of applicability of the traditional method of testing the homogeneity based on the use of Student's t-statistic, as well as more up-to-date methods. We describe a probabilistic model of generation of statistical data in the problem of testing the homogeneity of two independent samples. In terms of this model the concept of "homogeneity" ("no difference"), can be formalized in different ways. High degree of homogeneity is achieved if the two samples are taken from one and the same population (absolute homogeneity). In some cases it is advisable to testing the coincidence of some characteristics of the elements of the sample - mathematical expectations, medians, variances, coefficients of variation, and others (testing the homogeneity of characteristics). To test the homogeneity of mathematical expectations is often recommended classic t-test. It is believed that the samples taken from a normal distributions with equal variances. It is shown that for scientific, technical and economic data the preconditions of two-sample t-test usually are not performed. To test the homogeneity of mathematical expectations instead of t-test we have offered to use the Cramer-Welch test. We have considered the consistent nonparametric Smirnov and Lehmann-Rosenblatt tests for absolute homogeneity
The mathematical theory of classification contains a large number of approaches, models, methods, algorithms. This theory is very diverse. We distinguish three basic results in it - the best method of diagnosis (discriminant analysis), an adequate indicator of the quality of discriminant analysis algorithm, the statement about stopping after a finite number of steps iterative algorithms of cluster analysis. Namely, on the basis of Neyman - Pearson Lemma we have shown that the optimal method of diagnosis exists and can be expressed through probability densities corresponding to the classes. If the densities are unknown, one should use non-parametric estimators of training samples. Often, we use the quality indicator of diagnostic algorithm as "the probability (or share) the correct classification (diagnosis)" - the more the figure is the better algorithm is. It is shown that widespread use of this indicator is unreasonable, and we have offered the other - "predictive power", obtained by the conversion in the model of linear discriminant analysis. A stop after a finite number of steps of iterative algorithms of cluster analysis method is demonstrated by the example of k-means. In our opinion, these results are fundamental to the theory of classification and every specialist should be familiar with them for developing and applying the theory of classification
When considering the ecological safety of industrial productions, territory, etc., we usually allocate the constant (permanent) risk and the accident (emergency) risk. Permanent risk is given by the used technology, and cannot be changed substantially. Emergency risks are associated with uncertainty, in contrast to the constant risks. Let in adopted mathematical model the uncertainty is probabilistic in nature, and the loss describes as one-dimensional random variable. The distribution function of the loss, as a rule, is not normal. We have discussed in detail the seven characteristics of accidental loss: expectation; median and, more generally, quantile; dispersion; standard deviation; coefficient of variation; a linear combination of the expectation and standard deviation; the expectation of the loss function. Risk management may be to minimize these characteristics and their combinations (in different variants of multicriteria optimization). For example, in the two-criteria formulation it is required to minimize the expectation of loss and the standard deviation. Two-criteria formulation one way or another is reduced to a one-criteria formulation. In addition to probabilistic methods of risk modeling, sometimes we consider methods for describing risk using by means of objects of non-numeric nature, in particular qualitative characteristics, concepts of the theory of fuzzy sets, interval mathematical and econometric models and other mathematical tools. The main problems of the theory and practice of ecological insurance have been discussed
Controlling 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 information-analytical and
methodological support to achieve their goals." The
controller is developing a decision-making 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
organizational-economic (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
organizational-economic 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
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
Of 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 well-established 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 h-index 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