Causal Inference in Econometrics (1st ed. 2016) (Studies in Computational Intelligence #622)
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- Synopsis
- This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.
- Copyright:
- 2016
Book Details
- Book Quality:
- Publisher Quality
- ISBN-13:
- 9783319272849
- Related ISBNs:
- 9783319272832
- Publisher:
- Springer International Publishing
- Date of Addition:
- 09/14/19
- Copyrighted By:
- Springer International Publishing, Cham
- Adult content:
- No
- Language:
- English
- Has Image Descriptions:
- No
- Categories:
- Nonfiction, Computers and Internet, Technology, Mathematics and Statistics
- Submitted By:
- Bookshare Staff
- Usage Restrictions:
- This is a copyrighted book.
- Edited by:
- Van-Nam Huynh
- Edited by:
- Vladik Kreinovich
- Edited by:
- Songsak Sriboonchitta
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- by Van-Nam Huynh
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- by Songsak Sriboonchitta
- in Nonfiction
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- in Mathematics and Statistics