Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 117,43
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Aggiungi al carrelloCondizione: New. In.
Da: moluna, Greven, Germania
EUR 118,64
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. First statistical book to systematically deal with these time series data transformationsFirst statistical book to systematically deal with these time series data transformationsTime series play a crucial role in modern economies at all le.
Da: Books Puddle, New York, NY, U.S.A.
EUR 124,99
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Aggiungi al carrelloCondizione: New. pp. 428.
Da: Majestic Books, Hounslow, Regno Unito
EUR 127,04
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Aggiungi al carrelloCondizione: New. pp. 428 101 Illus.
Da: HPB-Red, Dallas, TX, U.S.A.
EUR 71,20
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Aggiungi al carrellopaperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 103,81
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Aggiungi al carrelloCondizione: New.
Editore: Springer New York Mai 2006, 2006
ISBN 10: 0387311025 ISBN 13: 9780387311029
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 162,93
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - In modern economies, time series play a crucial role at all levels of activity. They are used by decision makers to plan for a better future, by governments to promote prosperity, by central banks to control inflation, by unions to bargain for higher wages, by hospital, school boards, manufacturers, builders, transportation companies, and by consumers in general.A common misconception is that time series data originate from the direct and straightforward compilations of survey data, censuses, and administrative records. On the contrary, before publication time series are subject to statistical adjustments intended to facilitate analysis, increase efficiency, reduce bias, replace missing values, correct errors, and satisfy cross-sectional additivity constraints. Some of the most common adjustments are benchmarking, interpolation, temporal distribution, calendarization, and reconciliation.This book discusses the statistical methods most often applied for such adjustments, ranging from ad hoc procedures to regression-based models. The latter are emphasized, because of their clarity, ease of application, and superior results. Each topic is illustrated with many real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed, a real data example, the Canada Total Retail Trade Series, is followed throughout the book.This book brings together the scattered literature on these topics and presents them using a consistent notation and a unifying view. The book will promote better procedures by large producers of time series, e.g. statistical agencies and central banks. Furthermore, knowing what adjustments are made to the data and what technique is used and how they affect the trend, the business cycles and seasonality of the series, will enable users to perform better modeling, prediction, analysis and planning.This book will prove useful to graduate students and final year undergraduate students of time series and econometrics, as well as researchers and practitioners in government institutions and business. From the reviews:'It is an excellent reference book for people working in this area.' B. Abraham for Short Book Reviews of the ISI, December 2006.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 175,62
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Aggiungi al carrelloPaperback. Condizione: Like New. Like New. book.
Editore: Springer-Verlag New York Inc., 2006
ISBN 10: 0387311025 ISBN 13: 9780387311029
Lingua: Inglese
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 136,45
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Aggiungi al carrelloPaperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 627.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 161,26
Convertire valutaQuantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 428.