Modelling Non-Stationary Economic Time Series, S. Burke; J. Hunter

Автор: Simon P. Burke; John Hunter; Alessandra Canepa
Название: Multivariate Modelling of Non-Stationary Economic Time Series
ISBN: 0230243312 ISBN-13(EAN): 9780230243316
Издательство: Springer
Цена: 8384.00 р.
Наличие на складе: Есть у поставщикаПоставка под заказ.
Описание: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models.

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521139813 ISBN-13(EAN): 9780521139816
Издательство: Cambridge Academ
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Цена: 11722.00 р.
Наличие на складе: Ожидается поступление.

Описание: This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments estimation, nonparametric estimation and estimation by simulation.

Автор: Terence C. Mills
Название: The Econometric Modelling of Financial Time Series
ISBN: 052171009X ISBN-13(EAN): 9780521710091
Издательство: Cambridge Academ
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Цена: 7445.00 р.
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Описание: This best-selling graduate textbook provides detailed coverage of the latest research techniques and findings relating to the empirical analysis of financial markets. This third edition contains a wealth of material reflecting the developments of the last decade, including a new chapter on nonlinearity and its testing.

Автор: Granger Clive William John, Hatanaka Michio, Granger C. W. J.
Название: Spectral Analysis of Economic Time Series. (Psme-1)
ISBN: 069162478X ISBN-13(EAN): 9780691624785
Издательство: Wiley
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Цена: 6653.00 р.
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Описание: The important data of economics are in the form of time series; therefore, the statistical methods used will have to be those designed for time series data. New methods for analyzing series containing no trends have been developed by communication engineering, and much recent research has been devoted to adapting and extending these methods so that

Автор: Franses
Название: Time Series Models for Business and Economic Forecasting
ISBN: 0521817706 ISBN-13(EAN): 9780521817707
Издательство: Cambridge Academ
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Цена: 14890.00 р.
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Описание: With a new author team contributing decades of practical experience, this fully updated second edition textbook summarises the most critical decisions, techniques and steps in creating effective forecasting models. Includes all new theoretical and practical exercises geared at guiding students through the steps of creating forecasting models on their own.

Автор: Franses
Название: Time Series Models for Business and Economic Forecasting
ISBN: 0521520916 ISBN-13(EAN): 9780521520911
Издательство: Cambridge Academ
Рейтинг:
Цена: 7445.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: With a new author team contributing decades of practical experience, this fully updated second edition textbook summarises the most critical decisions, techniques and steps in creating effective forecasting models. Includes all new theoretical and practical exercises geared at guiding students through the steps of creating forecasting models on their own.

Автор: Mills
Название: Modelling Trends and Cycles in Economic Time Series
ISBN: 1403902097 ISBN-13(EAN): 9781403902092
Издательство: Springer
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Цена: 9781.00 р.
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Описание: Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s.

Автор: Terasvirta Clive W J
Название: Modelling Nonlinear Economic Time Series
ISBN: 0199587159 ISBN-13(EAN): 9780199587155
Издательство: Oxford Academ
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Цена: 6572.00 р.
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Описание: This volume is a comprehensive assessment of many recent developments in the modelling of time series. The focus is on introducing various nonlinear models and discussing their practical use, and encouraging the reader to apply nonlinear models to their practical modelling problems.

Автор: I.B. MacNeill; G. Umphrey
Название: Time Series and Econometric Modelling
ISBN: 9401086249 ISBN-13(EAN): 9789401086240
Издательство: Springer
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Цена: 20962.00 р.
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Описание: On May 27-31, 1985, a series of symposia was held at The University of Western Ontario, London, Canada, to celebrate the 70th birthday of Pro- fessor V.

Автор: Simon P. Burke; John Hunter; Alessandra Canepa
Название: Multivariate Modelling of Non-Stationary Economic Time Series
ISBN: 0230243304 ISBN-13(EAN): 9780230243309
Издательство: Springer
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Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models.

Автор: Simon P. Burke; John Hunter; Alessandra Canepa
Название: Multivariate Modelling of Non-Stationary Economic Time Series
ISBN: 0230243312 ISBN-13(EAN): 9780230243316
Издательство: Springer
Рейтинг:
Цена: 8384.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book examines conventional time series in the context of stationary data prior to a discussion of cointegration, with a focus on multivariate models.

Автор: S. Burke; J. Hunter
Название: Modelling Non-Stationary Economic Time Series
ISBN: 140390202X ISBN-13(EAN): 9781403902023
Издательство: Springer
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Цена: 15372.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Co-integration, equilibrium and equilibrium correction are key concepts in modern applications of econometrics to real world problems.

Автор: Martin
Название: Econometric Modelling with Time Series
ISBN: 0521196604 ISBN-13(EAN): 9780521196604
Издательство: Cambridge Academ
Рейтинг:
Цена: 16474.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides a general framework for specifying, estimating and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalised method of moments estimation, nonparametric estimation and estimation by simulation.