АНАЛИЗ МНОГОМЕРНЫХ СТАТИСТИЧЕСКИХ МОДЕЛЕЙ С НЕОДНОРОДНОЙ СТРУКТУРОЙ В СЛУЧАЕ СКРЫТОЙ МАРКОВСКОЙ ЗАВИСИМОСТИ СОСТОЯНИЙ

For vector autoregressive model with heterogeneous endogenous-exogenous structure and Markov switching states we propose the EM-algorithm for mixture decomposition, as well as discriminant analysis algorithm for classification of new observations. Accuracy of the algorithms is examined by means of computer simulation experiments.Для моделей векторной авторегрессии с неоднородной эндогенно-экзогенной структурой и марковскими переключениями состояний предлагается EM-алгоритм расщепления смесей распределений авторегрессионных наблюдений, а также алгоритм дискриминантного анализа вновь поступающих наблюдений. Точность алгоритмов исследуется по- мощью компьютерного моделирования

Particle acoustic detection in gravitational wave aluminum resonant antennas

The results on cosmic rays detected by the gravitational antenna NAUTILUS have motivated an experiment (RAP) based on a suspended cylindrical bar, which is made of the same aluminum alloy as NAUTILUS and is exposed to a high energy electron beam. Mechanical vibrations originate from the local thermal expansion caused by warming up due to the energy lost by particles crossing the material. The aim of the experiment is to measure the amplitude of the fundamental longitudinal vibration at different temperatures. We report on the results obtained down to a temperature of about 4 K, which agree at the level of about 10% with the predictions of the model describing the underlying physical process.Comment: RAP experiment, 16 pages, 7 figure

Gold Nanoparticle-Based Surface-Enhanced Raman Scattering for Noninvasive Molecular Probing of Embryonic Stem Cell Differentiation

This study reports the use of gold nanoparticle-based surface-enhanced Raman scattering (SERS) for probing the differentiation of mouse embryonic stem (mES) cells, including undifferentiated single cells, embryoid bodies (EBs), and terminally differentiated cardiomyocytes. Gold nanoparticles (GNPs) were successfully delivered into all 3 mES cell differentiation stages without affecting cell viability or proliferation. Transmission electron microscopy (TEM) confirmed the localization of GNPs inside the following cell organelles: mitochondria, secondary lysosome, and endoplasmic reticulum. Using bright- and dark-field imaging, the bright scattering of GNPs and nanoaggregates in all 3 ES cell differentiation stages could be visualized. EB (an early differentiation stage) and terminally differentiated cardiomyocytes both showed SERS peaks specific to metabolic activity in the mitochondria and to protein translation (amide I, amide II, and amide III peaks). These peaks have been rarely identified in undifferentiated single ES cells. Spatiotemporal changes observed in the SERS spectra from terminally differentiated cardiomyocyte tissues revealed local and dynamic molecular interactions as well as transformations during ES cell differentiation

Multi-country analysis of the COVID-19 pandemic typology using machine learning and neural network algorithms

The paper presents the results of a multi-country analysis of the intensity typology of the COVID-19 pandemic in 30 countries of the European region based on publicly available and regularly updated panel data for the entire period 2020-2022 of high pandemic activity. In the generated space of classification features, using cluster analysis algorithms, all countries are divided into three classes, which differ in the intensity of the epidemic process. Based on the obtained country ratings, an integral statistical indicator of the COVID-19 pandemic is constructed. A set of discriminant analysis machine learning and neural network algorithms are used to estimate current as well predict the expected class of the epidemic state based on the newly acquiring data

Statistical Estimation and Testing of Turning Points in Multivariate Regime-Switching Models

SECTION 4 ECONOMETRIC MODELING AND FINANCIAL MATHEMATIC

Analysis of the Banking Crises by the Panel Logit Model with the Application to Belarussian Banking System

This paper is devoted to the problem of forecasting of the banking crisis on the base of logit model of binary choise for panel data. The model based on the data for 60 countries,including Belarus, is constructed. The possibility of using of this model in the system of early warning is assessed

Evaluation of Forecasting Algorithms for Multivariate Econometric Models with Structural Breaks in the Forecasting Period

The paper is devoted to the problem of construction and accuracy evaluation of forecasting algorithms for multivariate econometric models in the assumption of structural break in the forecasting period

Analysis of the Banking Crises by the Panel Logit Model with the Application to Belarussian Banking System

This paper is devoted to the problem of forecasting of the banking crisis on the base of logit model of binary choise for panel data. The model based on the data for 60 countries,including Belarus, is constructed. The possibility of using of this model in the system of early warning is assessed