Applied nonlinear time series analysis: applications in physics, physiology and finance

The tools application in the areas: quantitative measures of nonlinear dynamics, Monte-Carlo statistical hypothesis testing, nonlinear modeling. The method of surrogate data. Estimation of correlation dimension. Times series embedding and reconstruction.

Подобные документы

  • A method for obtaining nonlinear dependencies of type, which based on the use of the function of linearizing the numerical dependencies of spreadsheets. Approximation for the conversion degree of a chemical reaction as a function of 2-3 parameters.

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  • Application of mathematical and statistical means for adaptation of the enterprise to changes. Theoretical and methodological substantiation of mathematical and statistical methods, models and tools of this process. Evaluation of its effectiveness.

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  • Transformation of model equations and analysis. The mathematical model that explores the dynamics of the impact of the use of condom and therapeutic treatment simultaneously. Nonlinear differential equation system consisting in groups of the population.

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  • The likelihood ratio test is a test used to compare the fit of two models, one of which is a special case of the other. The test is based on the likelihood ratio, which expresses how many times more likely the data are under one model than the other.

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  • An empirical study of long-term interrelations and short-term adjustment mechanism when making consumer decisions by households in UA. The paper presents a statistical analysis of the dynamic properties of the series of consumption, income and inflation.

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  • The problem of studying the relationship of economic indicators in economic analysis. Construction of an econometric model of the ratio of the exchange rate of tenge to the ruble and the possibility of using it to forecast real economic processes.

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  • European options on several assets. The Black-Scholes-Merton model. Numerical method. Sparse grid combination technique. Applying the method to the option pricing problem. Solving the transformed equation. Monte Carlo simulations. Bermudan styles.

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  • The development of understanding the least squares and related statistical methods without becoming excessively mathematical. The review of key concepts in simple linear regression, matrix operations, and multiple regression. Geometric interpretations.

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  • Carrying out of econometric analysis by means of panel data models of the volume of innovative goods, works and services in the Russian Federation. The dependence on the number of personnel involved in scientific research and the internal expenses.

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  • Data Analysis and Model-Building Basics, making Predictions by Using Regression. Comparing Many Means with ANOVA. Building Strong Connections with Chi-Square Tests, rebels without a Distribution. Ten Errors in Statistical Conclusions, Practice Problems.

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  • Principles of functioning of small oil and gas enterprises in Russia. The main characteristics and socio-economic tasks performed by small oil and gas enterprises. Forecast calculations of the dynamics of hydrocarbon raw materials for the planning period.

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  • Investigation of the phenomenon of asymmetry in the Iranian economy. The study of the effects of inflation on monetary policy. Using the model of autoregressive conditional heteroscedasticity for describing of financial and macroeconomic time series.

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  • Measurement of potential losses in the value of the asset VaR. Approaches that are used to compute Value at Risk: the variance-covariance approach, the historical and the Monte Carlo simulations. Risk assessment value at risk as a qualitative tool.

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  • The potential loss in value of a risky asset or portfolio over a defined period for a given confidence interval. Historical and Monte Carlo Simulation. Value at Risk as a risk assessment tool at banks and other financial service firms in the last decade.

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  • Analyze the efficiency and the overall performance of Turkish airports using the data envelopment analysis. Efficiency scores under constant returns to scale. Indentifying the most and least efficient airports in Turkey using data envelopment analysis.

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  • Effective forecasting of the economy - one of the most urgent scientific, political and social problems. Presenting several scenarios of forecasts considering different changes in separate parameters like the crucial functions of economic modeling.

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  • The mathematical model of free market of three goods in the conditions of supply lag in the interval of discrete time with market parameters, demand vector and initial conditions is considered. The dynamics of allowable profit of the seller is obtained.

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  • Consideration of mathematical modeling of the immune system in the process of disease with the immunodeficiency virus without treatment. Investigation of the dynamics of infection. Evaluation of the rate of reproduction of the virus in the blood.

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  • Questions modeling wood figures. Construction of models under extreme conditions. Processes of heat transfer in extreme mode. Growth, heat and wave processes, diffusion. Normed spaces and lots of variety. Transformations generated by model numbers tree.

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  • Econometric approaches to modeling censored demand - a tool that is used to obtain consistent and unbiased parameter estimates. The neglect of censored data when building a forecast - a significant lack of demand analysis by machine learning methods.

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  • In the article describes the current state of agent-based modeling of geographic space and spatial economic systems. It also reveals the reasons why this approach to modeling such phenomena is of particular interest. The review of approaches is given.

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  • Study of the growth of fullerenes and carbon nanotubes from small clusters. Choice of interatomic potential as a key factor in molecular dynamics modeling. Fullerene assembly from graphite fragments. Structure evolution of reaction the materials.

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