Editors:
- Presents recent research on Predictive Econometrics and Big Data
- Introduces readers to the theoretical foundations and applications
- Written by respected experts in the field
- Includes edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018
Part of the book series: Studies in Computational Intelligence (SCI, volume 753)
Conference series link(s): TES: International Conference of the Thailand Econometrics Society
Conference proceedings info: TES 2018.
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (55 papers)
-
Front Matter
-
Keynote Address
-
Front Matter
-
-
Fundamental Theory
-
Front Matter
-
About this book
This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems.
Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.
Editors and Affiliations
-
Computer Science Department, University of Texas at El Paso, El Paso, USA
Vladik Kreinovich
-
International College, Chiang Mai University, Chiang Mai, Thailand
Songsak Sriboonchitta, Nopasit Chakpitak
Bibliographic Information
Book Title: Predictive Econometrics and Big Data
Editors: Vladik Kreinovich, Songsak Sriboonchitta, Nopasit Chakpitak
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-70942-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Hardcover ISBN: 978-3-319-70941-3Published: 02 December 2017
Softcover ISBN: 978-3-319-89018-0Published: 04 September 2018
eBook ISBN: 978-3-319-70942-0Published: 30 November 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XII, 780
Number of Illustrations: 146 b/w illustrations
Topics: Computational Intelligence, Artificial Intelligence, Econometrics