Complex-valued Econometrics With Examples in R: Modelling, Regression and Applications - Rilegato

Svetunkov, Sergey; Svetunkov, Ivan

Rilegato

ISBN 10: 3031626079 ISBN 13: 9783031626074

Casa editrice: Springer Nature, 2024

Riassunto

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.

Su questo libro

Informazioni sull'autore

Sergey Svetunkov, PhD in Economics, Doctor of Economic Sciences, Professor at the Peter the Great St. Petersburg Polytechnic University, is the leading expert in the field of mathematical modelling in economics and economic forecasting. He is an author of more than 250 scientific publications. Over the last few decades, he has also acted as an expert of the Russian Science Foundation.

Ivan Svetunkov is a Lecturer of Marketing Analytics at Lancaster University, UK. He has PhD in Management Science from Lancaster University and a candidate degree in economics from Saint Petersburg State University of Economics and Finance. His main area of interest is statistical learning for forecasting, focusing on demand forecasting in healthcare, supply chains and retail. He is a creator and a maintainer of several forecasting- and analytics-related R packages and an author of many papers and a monograph “Forecasting and Analytics with the Augmented Dynamic Adaptive Model”.

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: Springer Nature
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 3031626079
• ISBN 13: 9783031626074
• Rilegatura: Copertina rigida
• Numero di pagine: 168
• Contatto del produttore: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Germania