Data Analysis and Classification: Methods and Applications - Brossura

Brossura

ISBN 10: 3030751899 ISBN 13: 9783030751890

Casa editrice: Springer, 2021

Riassunto

This volume gathers peer-reviewed contributions that address a wide range of recent developments in the methodology and applications of data analysis and classification tools in micro and macroeconomic problems. The papers were originally presented at the 29th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2020, held in Sopot, Poland, September 7–9, 2020. Providing a balance between methodological contributions and empirical papers, the book is divided into five parts focusing on methodology, finance, economics, social issues and applications dealing with COVID-19 data. It is aimed at a wide audience, including researchers at universities and research institutions, graduate and doctoral students, practitioners, data scientists and employees in public statistical institutions.

Su questo libro

Informazioni sull?autore

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, and he is an author of numerous international and regional publications, including 18 books.

Krzysztof Najman is an Associate Professor at the University of Gdańsk, Poland and Deputy Dean for Student Affairs and Education of the Faculty of Management. He is a member of the Main Council of the Polish Statistical Association and its Section of Classification and Data Analysis (SKAD). His scientific interests include cluster analysis and classification methods, artificial intelligence models, self-learning neural networks, multivariate statistical analysis, and data mining. He is an author of numerous international and regional publications, including 1 book.

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, and he has authored numerous publications, including 11 books.

Dalla quarta di copertina

This volume gathers peer-reviewed contributions that address a wide range of recent developments in the methodology and applications of data analysis and classification tools in micro and macroeconomic problems. The papers were originally presented at the 29th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2020, held in Sopot, Poland, September 7–9, 2020. Providing a balance between methodological contributions and empirical papers, the book is divided into five parts focusing on methodology, finance, economics, social issues and applications dealing with COVID-19 data. It is aimed at a wide audience, including researchers at universities and research institutions, graduate and doctoral students, practitioners, data scientists and employees in public statistical institutions.

Dettagli dell'edizione

• Editore: Springer
• Data di pubblicazione: 2021
• Lingua: Inglese
• ISBN 10: 3030751899
• ISBN 13: 9783030751890
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 368
• Redattore: Jajuga Krzysztof, Najman Krzysztof, Walesiak Marek
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