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_aCausal Inference in Econometrics _h[electronic resource] / _cedited by Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta. |
250 | _a1st ed. 2016. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
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300 |
_aXI, 638 p. 106 illus., 91 illus. in color. _bonline resource. |
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490 | 1 |
_aStudies in Computational Intelligence, _x1860-9503 ; _v622 |
|
520 | _aThis 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. | ||
650 | 0 |
_aComputational intelligence. _97716 |
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_aSocial sciences—Mathematics. _931863 |
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_aSecurity systems. _931879 |
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_aComputational Intelligence. _97716 |
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_aMathematics in Business, Economics and Finance. _931864 |
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_aSecurity Science and Technology. _931884 |
700 | 1 |
_aHuynh, Van-Nam. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _962828 |
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_aKreinovich, Vladik. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _962829 |
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_aSriboonchitta, Songsak. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _962830 |
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_aSpringerLink (Online service) _962831 |
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