Regression on the basis of nonstationary Gaussian processes with Bayesian regularization
We consider the regression problem, i.e. prediction of a real valued function. A Gaussian process prior is imposed on the function, and is combined with the training data to obtain predictions for new points. We introduce a Bayesian regularization on parameters of a covariance function of the process, which increases quality of approximation and robustness of the estimation. Also an approach to modeling nonstationary covariance function of a Gaussian process on basis of linear expansion in parametric functional dictionary is proposed. Introducing such a covariance function allows to model functions, which have non-homogeneous behaviour. Combining above features with careful optimization of covariance function parameters results in unified approach, which can be easily implemented and applied. The resulting algorithm is an out of the box solution to regression problems, with no need to tune parameters manually. The effectiveness of the method is demonstrated on various datasets.
Regression, cluster and component analysis of economic globalization of several developed economies is conducted with the purpose to find out the level of international trade globalization. 4 clusters on the basis of trade balance in goods, trade balance in services, FDI are found out.
This book presents a systematic exposition of the modern theory of Gaussian measures. The basic properties of finite and infinite dimensional Gaussian distributions, including their linear and nonlinear transformations, are discussed. The book is intended for graduate students and researchers in probability theory, mathematical statistics, functional analysis, and mathematical physics. It contains a lot of examples and exercises. The bibliography contains 844 items; the detailed bibliographical comments and subject index are included.
On the Russian market of insurance services life insurance is one of the fastest growing segments. Identifying among the clients of the insurance company risk groups composed of individuals more prone to other termination of the contract of life insurance, allows to conduct purposeful work on their retention, which ultimately should lead to reduction of customer churn and, as a consequence, have a positive impact on the financial performance of the insurance company. The solution is achieved through the development of a model that predicts premature termination of life insurance contracts. In this work a comparative analysis of regression models and neural network models the termination of contracts of life insurance.
The given research is devoted to the acute issue of efficiency of valuable assets positioning carried out by commercial banks. The paper is aimed at examining factors which affect the efficiency of securities placement by commercial banks, as well as an econometric analysis based on the least squares method of the significance of the selected factors and their impact on the efficiency indicator. While researching this issue the phenomenon of adaptability, which means the higher the price set is in comparison with the medium price scale the higher the underpricing at setting with corresponding other equal terms, was singled out The methods of critical literature review, statistical analysis, and econometric model creation have been used to justify it. Moreover, the research resulted in model creation which characterizes the state of a definite commercial bank to be ready for emission of assets by means of initial public offering.
The paper explores theoretical approaches to the company IPO underpricing and analyzes capital structure impact on the underpricing of the Russian issuers.
This article describes the new Stata command xml_tab, which outputs the results of estimation commands and Stata matrices directly into tables in XML format. The XML files can be opened with Microsoft Excel or OpenOffice Calc, or they can be linked with Microsoft Word files. By using XML, xml_tab allows Stata users to apply a rich set of formatting options to the elements of output tables.
Measuring indirect importance of various attributes is a very common task in marketing analysis for which researchers use correlation and regression techniques. We have listed and illustrated some common problems with widely used latent importance measures. A more theoretically sound approach – the Shapley Value decomposition – was applied to a rich data set of US internet stores. The use of store-level data instead of respondent-level data allowed us to reveal the factors, which are powerful in explaining, why some stores have higher rates of willingness to make repeat purchases than the others. By confronting the indirect importance and performance measures for three different internet stores, we have revealed strengths, weaknesses, attributes that the company should bring customers’ attention to and attributes improvement of which is not of a high priority.
The textbook has passed practical tests and written on the basis of the readable authors for many years. Presented in textbook materials give students orientation in the solution of many practical problems in a number of areas, constitute the initial level to obtain a broader and deeper education in the field of probability theory. The book provides an overview of the theory of stochastic processes, detailed material on the theory of Markov processes with discrete time (Markov chains) and continuous-time. In addition to the solved problems for each Chapter of the textbook suggested problems to solve and theoretical questions to test the quality of the learning material.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.