This reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting multiple time series. The models covered include vector autoregressive, cointegrated, vector autoregressive moving average, multivariate ARCH and periodic processes as well as dynamic simultaneous equations and state space models. Least squares, maximum likelihood and Bayesian methods are considered for estimating these models. Different procedures for model selection and model specification are treated and a wide range of tests and criteria for model checking are introduced. Causality analysis, impulse response analysis and innovation accounting are presented as tools for structural analysis. The book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their tasks. It bridges the gap to the difficult technical literature on the topic.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
This reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting multiple time series. The models covered include vector autoregressive, cointegrated, vector autoregressive moving average, multivariate ARCH and periodic processes as well as dynamic simultaneous equations and state space models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection and model specification are treated and a wide range of tests and criteria for model checking are introduced. Causality analysis, impulse response analysis and innovation accounting are presented as tools for structural analysis.The book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their tasks. It bridges the gap to the difficult technical literature on the topic.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : World of Books (was SecondSale), Montgomery, IL, Etats-Unis
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Broschiert. Etat : Gut. 764 Seiten Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 1180. N° de réf. du vendeur 2305390
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Vendeur : Skoob-ebooks, Pontiac, QC, Canada
Softcover. Etat : Good. Minor wear. Some pages have a little highlighting (approximately 5% to 10% of the pages). Cover has few signs of wear. 30-day returns. Shipments destined outside Canada may be subject to duties where the customer resides. ; 6.1 X 1.78 X 9.25 inches; 764 pages; R0 540k/1m s0. N° de réf. du vendeur 8601
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Vendeur : GoldBooks, Denver, CO, Etats-Unis
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Vendeur : medimops, Berlin, Allemagne
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Vendeur : medimops, Berlin, Allemagne
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Vendeur : Anybook.com, Lincoln, Royaume-Uni
Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1250grams, ISBN:9783540262398. N° de réf. du vendeur 8652886
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Vendeur : BennettBooksLtd, Los Angeles, CA, Etats-Unis
paperback. Etat : New. In shrink wrap. Looks like an interesting title! N° de réf. du vendeur Q-3540262393
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