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A01=Ivan Svetunkov
A01=Sergey Svetunkov
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Author_Ivan Svetunkov
Author_Sergey Svetunkov
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Category=KJT
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Complex-Valued Econometrics with Examples in R: Modelling, Regression and Applications

★★★★★
★★★★★

English

By (author): Ivan Svetunkov Sergey Svetunkov

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.

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A01=Ivan SvetunkovA01=Sergey SvetunkovAge Group_UncategorizedAuthor_Ivan SvetunkovAuthor_Sergey Svetunkovautomatic-updateCategory1=Non-FictionCategory=KCACategory=KCHCategory=KCHSCategory=KJMDCategory=KJTCategory=PBTCategory=UFMCOP=SwitzerlandDelivery_Pre-orderLanguage_EnglishPA=Not yet availablePrice_€50 to €100PS=Activesoftlaunch

Will deliver when available. Publication date 16 Aug 2024

Product Details
  • Dimensions: 155 x 235mm
  • Publication Date: 26 Jul 2024
  • Publisher: Springer International Publishing AG
  • Publication City/Country: Switzerland
  • Language: English
  • ISBN13: 9783031626074

About Ivan SvetunkovSergey Svetunkov

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.

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