Studies in Computational Intelligence

Predictive Econometrics and Big Data

Editors: Kreinovich, Vladik, Sriboonchitta, Songsak, Chakpitak, Nopasit (Eds.)

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  • 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
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eBook 223,63 €
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  • ISBN 978-3-319-70942-0
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Hardcover 395,19 €
price for Spain (gross)
  • ISBN 978-3-319-70941-3
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Softcover 279,76 €
price for Spain (gross)
  • ISBN 978-3-319-89018-0
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
  • The final prices may differ from the prices shown due to specifics of VAT rules
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.

Table of contents (55 chapters)

Table of contents (55 chapters)
  • Data in the 21st Century

    Pages 3-17

    Baru, Chaitanya

  • Model-Assisted Survey Estimation with Imperfectly Matched Auxiliary Data

    Pages 21-35

    Breidt, F. Jay (et al.)

  • COBra: Copula-Based Portfolio Optimization

    Pages 36-77

    Paolella, Marc S. (et al.)

  • Multiple Testing of One-Sided Hypotheses: Combining Bonferroni and the Bootstrap

    Pages 78-94

    Romano, Joseph P. (et al.)

  • Exploring Message Correlation in Crowd-Based Data Using Hyper Coordinates Visualization Technique

    Pages 95-121

    Cao, Tien-Dung (et al.)

Buy this book

eBook 223,63 €
price for Spain (gross)
  • ISBN 978-3-319-70942-0
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 395,19 €
price for Spain (gross)
  • ISBN 978-3-319-70941-3
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 279,76 €
price for Spain (gross)
  • ISBN 978-3-319-89018-0
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Predictive Econometrics and Big Data
Editors
  • Vladik Kreinovich
  • Songsak Sriboonchitta
  • Nopasit Chakpitak
Series Title
Studies in Computational Intelligence
Series Volume
753
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG, part of Springer Nature
eBook ISBN
978-3-319-70942-0
DOI
10.1007/978-3-319-70942-0
Hardcover ISBN
978-3-319-70941-3
Softcover ISBN
978-3-319-89018-0
Series ISSN
1860-949X
Edition Number
1
Number of Pages
XII, 780
Number of Illustrations
146 b/w illustrations
Topics