Статистические подходы к анализу и прогнозированию демографических данных
Introduction. Possibilities of application ARIMA-models to analysis and forecasting of demographic time series were considered in the article. Foreign studies had shown that the ARIMA-models give good results for forecasting indicators such as population, birth rates and death rates, life expectancy, along with the traditional demographic methods (cohort-component approach). Research technique. Box-Jenkins methodology of the analysis and forecasting of time series, particularly with regard to demographic data: total fertility rate in Russia (1990-2014), the number of marriages by months in Russia (2005-2015), total fertility rate in France (1740-2014) and the unemployment rate in Russia (1996-2016) was used in the work. ARIMA, ARIMA and ARIMA-models, depending on the nature of the dynamics of the studied indicators were analyzed. Results. The analysis had shown that the estimated ARIMA-models for the total fertility rate and number of marriages were adequate and had good statistical and prognostic properties. Forecasts were built on basis of the obtained models. In the case of long series availability of properties with a long memory processes have not been identified.
In this update, we present the new version of the random number generator (RNG) library RNGSSELIB,which, in particular, contains fast SSE realizations of a number of modern and most reliable generators . The new features are: (i) Fortran compatibility and examples of using the library in Fortran; (ii) new modern and reliable generators; (iii) the abilities to jump ahead inside a RNG sequence and to initialize up to 1019 independent random number streams with block splitting method.
The manual includes the general orientation information on quantitative and qualitative methods, necessary for experts without basic administrative education. With basic education the manual will be useful for experts not only expansion and fixing of knowledge, but also the annex to actual problems of the organization and management. Its feature that it assumes updating, fixing and judgment of knowledge of the subjects studied earlier, on other forms and training steps. The manual will have practical value for the students who are training on master programs for the Management direction.
To large organizations, business intelligence (BI) promises the capability of collecting and analyzing internal and external data to generate knowledge and value, thus providing decision support at the strategic, tactical, and operational levels. BI is now impacted by the “Big Data” phenomena and the evolution of society and users. In particular, BI applications must cope with additional heterogeneous (often Web-based) sources, e.g., from social networks, blogs, competitors’, suppliers’, or distributors’ data, governmental or NGO-based analysis and papers, or from research publications. In addition, they must be able to provide their results also on mobile devices, taking into account location-based or time-based environmental data. The lectures held at the Third European Business Intelligence Summer School (eBISS), which are presented here in an extended and refined format, cover not only established BI and BPM technologies, but extend into innovative aspects that are important in this new environment and for novel applications, e.g., pattern and process mining, business semantics, Linked Open Data, and large-scale data management and analysis. Combining papers by leading researchers in the field, this volume equips the reader with the state-of-the-art background necessary for creating the future of BI. It also provides the reader with an excellent basis and many pointers for further research in this growing field.
This paper considers a seasonal adjustment procedure that is capable of preparing data to the use in applied general equilibrium models. It is shown that standard seasonal adjustment procedures do not satisfy the property of invariance to deflating, that hinders their use in applied general equilibrium models. A system of axioms that describes the desired properties of a seasonal adjustment procedure is suggested. The impossibility of simultaneous fulfillment of additivity and invariance to deflation properties is shown. Therefore, one needs to choose the desired property depending on the type of the task that is solved. The proposed procedure models the seasonality as a set of seasonal multiplicative dummy variables, so it can not only remove the seasonality, but also return it to the data in order to obtain forecasts. The procedure also has a built-in outlier detector, which enables it to handle noise and outliers in data of different types. It is compared to the popular X12 seasonal adjustment procedure using Monte-Carlo method. It is shown that the preciseness of the proposed procedure is comparable to X12 in terms of resistance to outliers and preservation of statistical properties of the series in the specific set of problems connected to the estimation of general equilibrium models. Several examples of its application to real data are shown. The obtained results allow us to make a conclusion about applicability of the suggested procedure to the removal of seasonality from the data that is used in the estimation of macroeconomic models.
The main goal of this paper is to study interconnections between credit ratings and financial indicators of industrial companies from BRICS countries. We use method of patterns, one of the modern methods of nonlinear modeling, to identify groups of heterogeneous objects with different influence on ratings. Additionally, in this research, we evaluate Tobit regression model for selected groups and establish some credit rating patterns for the BRICS industrial companies. Our results of Tobin model, may have practical implementation in short-term financial management.
We present the random number generator (RNG) library RNGAVXLIB, which contains fast AVX realizations of a number of modern random number generators, and also the abilities to jump ahead inside a RNG sequence and to initialize up to 1019 independent random number streams with block splitting method. Fast AVX implementations produce exactly the same output sequences as the original algorithms. Usage of AVX vectorization allows to substantially improve performance of the generators. The new realizations are up to 2 times faster than the SSE realizations implemented in the previous version of the library (Barash and Shchur, 2013), and up to 40 times faster compared to the original algorithms written in ANSI C.
We consider certain spaces of functions on the circle, which naturally appear in harmonic analysis, and superposition operators on these spaces. We study the following question: which functions have the property that each their superposition with a homeomorphism of the circle belongs to a given space? We also study the multidimensional case.
We consider the spaces of functions on the m-dimensional torus, whose Fourier transform is p -summable. We obtain estimates for the norms of the exponential functions deformed by a C1 -smooth phase. The results generalize to the multidimensional case the one-dimensional results obtained by the author earlier in “Quantitative estimates in the Beurling—Helson theorem”, Sbornik: Mathematics, 201:12 (2010), 1811 – 1836.
We consider the spaces of function on the circle whose Fourier transform is p-summable. We obtain estimates for the norms of exponential functions deformed by a C1 -smooth phase.