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020 _a9783319272849
040 _aES-MaUEC
050 4 _aHB139
_b.C387 2016
082 0 4 _a006.3
245 1 0 _aCausal Inference in Econometrics
_cedited by Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta
250 _a1st ed.
260 _aCham
_bSpringer International Publishing
_c2016
300 _a1 recurso en línea (XI, 638 páginas)
_b106 ilustraciones, 15 ilustraciones en color
336 _aTexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
490 0 _aStudies in Computational Intelligence
_x1860-949X
_v622
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.
650 7 _aEconomía matemática
_0comprobar BNE19900986429
_2embne
_9140530
700 1 _aHuynh, Van-Nam
_eeditor literario
_0Local
_998176
700 1 _aKreinovich, Vladik
_eeditor literario
_0Local
_998177
700 1 _aSriboonchitta, Songsak.
_eeditor literario
_998178
_0Local
710 2 _aSpringerLink (Online service)
_0Local
_9106996
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-27284-9
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901 _ai9783319272849
907 _a.b12945821
_b10-10-17
_c21-11-16
942 _2lcc
_cLE
945 _aHB139 .C387 2016 EB
_g1
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988 _aEBOOK, asignarmaterias , EBSPRINGER
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