Complex-Valued Econometrics with Examples in R
Modelling, Regression and Applications
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Beschreibung
This book explores the application of complex variables to econometric modeling. Providing a thorough introduction to the theory of complex numbers, it extends these concepts to develop complex-valued models that enhance the accuracy and depth of economic forecasting and data analysis. From simple to multiple complex linear regression, the monograph discusses model formulation, estimation techniques, and correlation analysis, supported by examples in R.
This comprehensive guide is a useful resource for students, researchers, and practitioners aiming to apply advanced mathematical techniques to tackle complex real-life problems, making it a useful tool for enhancing predictive analytics in business, economics, and finance.
This book explores the application of complex variables to econometric modeling. Providing a thorough introduction to the theory of complex numbers, it extends these concepts to develop complex-valued models that enhance the accuracy and depth of economic forecasting and data analysis. From simple to multiple complex linear regression, the monograph discusses model formulation, estimation techniques, and correlation analysis, supported by examples in R.
This comprehensive guide is a useful resource for students, researchers, and practitioners aiming to apply advanced mathematical techniques to tackle complex real-life problems, making it a useful tool for enhancing predictive analytics in business, economics, and finance.
Offers an original approach to complex-valued autoregressions Presents new sections of mathematical statistics of a complex random variable Useful for the practice of modeling complex stochastic processes, including multidimensional processes
Autor*in
Sergey Svetunkov
Themen in »Complex-Valued Econometrics with Examples in R«
Complex variable functions Complex-valued economics Mathematical methods and models in economics Autoregression Vector autoregressions Mathematical statistics of a complex random variable Complex variation Modeling of stochastic processes Short term forecasting Complex-valued autoregressions Correlogram TCVF Stochastic reversible processes Forecasting