Causal Inference in Econometrics: Studies in Computational Intelligence, cartea 622
Editat de Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchittaen Limba Engleză Hardback – 6 ian 2016
To get agood understanding of the causal inference, it is important to have models ofeconomic phenomena which are as accurate as possible. Because of this need,this volume also contains papers that use non-traditional economic models, suchas fuzzy models and models obtained by using neural networks and data miningtechniques. It also contains papers that apply different econometric models toanalyze real-life economic dependencies.
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Specificații
ISBN-13: 9783319272832
ISBN-10: 3319272837
Pagini: 638
Ilustrații: XI, 638 p. 106 illus., 15 illus. in color.
Dimensiuni: 155 x 235 x 35 mm
Greutate: 1.08 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 3319272837
Pagini: 638
Ilustrații: XI, 638 p. 106 illus., 15 illus. in color.
Dimensiuni: 155 x 235 x 35 mm
Greutate: 1.08 kg
Ediția:1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Cham, Switzerland
Cuprins
Part I Fundamental Theory.- Part II Applications.
Textul de pe ultima copertă
This bookis devoted to the analysis of causal inference which is one of the most difficult tasks in dataanalysis: when two phenomena are observed to be related, it is often difficultto decide whether one of them causally influences the other one, or whetherthese two phenomena have a common cause. This analysis is the main focus ofthis volume.
To get agood understanding of the causal inference, it is important to have models ofeconomic phenomena which are as accurate as possible. Because of this need,this volume also contains papers that use non-traditional economic models, suchas fuzzy models and models obtained by using neural networks and data miningtechniques. It also contains papers that apply different econometric models toanalyze real-life economic dependencies.
To get agood understanding of the causal inference, it is important to have models ofeconomic phenomena which are as accurate as possible. Because of this need,this volume also contains papers that use non-traditional economic models, suchas fuzzy models and models obtained by using neural networks and data miningtechniques. It also contains papers that apply different econometric models toanalyze real-life economic dependencies.
Caracteristici
theoretical foundations and applications Written by experts in the field Presents recent research Includes supplementary material: sn.pub/extras