| 书目名称 | Robustness in Econometrics |
| 编辑 | Vladik Kreinovich,Songsak Sriboonchitta,Van-Nam Hu |
| 视频video | |
| 概述 | Presents recent research on robustness in econometrics.Introduces theoretical foundations and applications.Written by respected experts in the field.Includes supplementary material: |
| 丛书名称 | Studies in Computational Intelligence |
| 图书封面 |  |
| 描述 | 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.. |
| 出版日期 | Book 2017 |
| 关键词 | Computational Intelligence; Econometrics; Robustness; Robustness in Econometrics; Models of Economic Phe |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-50742-2 |
| isbn_softcover | 978-3-319-84480-0 |
| isbn_ebook | 978-3-319-50742-2Series ISSN 1860-949X Series E-ISSN 1860-9503 |
| issn_series | 1860-949X |
| copyright | Springer International Publishing AG 2017 |
发表于 2025-3-21 16:39:36
