书目名称 | Predictive Econometrics and Big Data |
编辑 | Vladik Kreinovich,Songsak Sriboonchitta,Nopasit Ch |
视频video | http://file.papertrans.cn/755/754588/754588.mp4 |
概述 | 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 pre |
丛书名称 | Studies in Computational Intelligence |
图书封面 |  |
描述 | .This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11.th. 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.. |
出版日期 | Conference proceedings 2018 |
关键词 | Computational Intelligence; Econometrics; Precitive Econometrics; Big Data; Models of Economic Phenomena |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-319-70942-0 |
isbn_softcover | 978-3-319-89018-0 |
isbn_ebook | 978-3-319-70942-0Series ISSN 1860-949X Series E-ISSN 1860-9503 |
issn_series | 1860-949X |
copyright | Springer International Publishing AG, part of Springer Nature 2018 |