Robustness in Econometrics

Lieferzeit: Lieferbar innerhalb 14 Tagen

181,89 

Studies in Computational Intelligence 692

ISBN: 3319507419
ISBN 13: 9783319507415
Herausgeber: Vladik Kreinovich/Songsak Sriboonchitta/Van-Nam Huynh
Verlag: Springer Verlag GmbH
Umfang: x, 705 S., 9 s/w Illustr., 120 farbige Illustr., 705 p. 129 illus., 120 illus. in color.
Erscheinungsdatum: 20.02.2017
Auflage: 1/2017
Produktform: Gebunden/Hardback
Einband: Gebunden

This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.

Artikelnummer: 405836 Kategorie:

Beschreibung

This book presents recent research on robustness in econometrics. Robust data processing techniques - i.e., techniques that yield results minimally affected by outliers - and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.

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E-Mail: juergen.hartmann@springer.com

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