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_aHB139 _b.C387 2016 |
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_aCausal Inference in Econometrics _cedited by Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta |
| 250 | _a1st ed. | ||
| 260 |
_aCham _bSpringer International Publishing _c2016 |
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| 300 |
_a1 recurso en línea (XI, 638 páginas) _b106 ilustraciones, 15 ilustraciones en color |
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_aStudies in Computational Intelligence _x1860-949X _v622 |
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| 520 | 3 | _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. | |
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_aEconomía matemática _0comprobar BNE19900986429 _2embne _9140530 |
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_aHuynh, Van-Nam _eeditor literario _0Local _998176 |
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_aKreinovich, Vladik _eeditor literario _0Local _998177 |
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_aSriboonchitta, Songsak. _eeditor literario _998178 _0Local |
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