Overview
- Presents the latest research on data analysis and classification tools for economic problems
- Features applications in economics, finance, social issues and to Covid-19 data
- Accessible to a wide audience, including researchers, data scientists and statisticians in statistical offices
Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization (STUDIES CLASS)
Included in the following conference series:
Conference proceedings info: SKAD 2021.
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Table of contents (25 papers)
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Front Matter
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Methods
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Front Matter
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Applications in Finance
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Front Matter
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Applications in Economics
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Front Matter
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Other volumes
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Modern Classification and Data Analysis
Keywords
About this book
This volume presents a selection of peer-reviewed papers that address the latest developments in the methodology and applications of data analysis and classification tools to micro- and macroeconomic problems. The contributions were originally presented at the 30th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2021, held online in Poznań, Poland, September 8–10, 2021.
Providing a balance between methodological and empirical studies, and covering a wide range of topics, the book is divided into five parts focusing on methods and applications in finance, economics, social issues and to COVID-19 data. The book is aimed at a wide audience, including researchers at universities and research institutions, PhD students, as well as practitioners, data scientists and employees in public statistical institutions.
Editors and Affiliations
About the editors
Krzysztof Jajuga is a Professor of Finance and Statistics and Chair of the Department of Financial Investments and Risk Management at the Wroclaw University of Economics and Business, Poland. He has been a Visiting Professor at several universities in the USA, Europe and China and holds an honorary doctorate from Cracow University of Economics and an honorary professorship from Warsaw University of Technology. His scientific interests include financial econometrics and financial markets, risk analysis and management, household finance and multivariate statistics.
Grażyna Dehnel is an Associate Professor at the Department of Statistics, Poznań University of Economics and Business, Poland. Her main research interests include small area estimation, classification and data analysis methods, survey sampling, and short-term and structural business statistics. She is also interested in outlier robust regression applied on business data and data integration.
Marek Walesiak is a Professor of Economics, and Chair of the Department of Econometrics and Computer Science at the Wroclaw University of Economics and Business, Poland. He is a member of the Methodological Commission and the Scientific Statistical Council in Statistics Poland (GUS) and an active member of many scientific professional bodies, including the Section of Classification and Data Analysis (SKAD). His scientific interests are in classification and data analysis, composite indicators, multivariate statistical analysis, marketing research, and computational techniques in R.
Bibliographic Information
Book Title: Modern Classification and Data Analysis
Book Subtitle: Methodology and Applications to Micro- and Macroeconomic Problems
Editors: Krzysztof Jajuga, Grażyna Dehnel, Marek Walesiak
Series Title: Studies in Classification, Data Analysis, and Knowledge Organization
DOI: https://doi.org/10.1007/978-3-031-10190-8
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Softcover ISBN: 978-3-031-10189-2Published: 16 October 2022
eBook ISBN: 978-3-031-10190-8Published: 16 October 2022
Series ISSN: 1431-8814
Series E-ISSN: 2198-3321
Edition Number: 1
Number of Pages: XV, 384
Number of Illustrations: 47 b/w illustrations, 88 illustrations in colour
Topics: Statistics for Business, Management, Economics, Finance, Insurance, Data Mining and Knowledge Discovery, Statistics for Social Sciences, Humanities, Law, Statistics, general, Computer Applications