Forecasting, Structural Time Series Models and the Kalman Filter

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Advanced econometrics meets practical time series analysis.

If you've been finding traditional econometrics disconnected from practical time series analysis, Andrew Harvey's work might be the bridge you've been looking for. It dives into the complexities of forecasting with a rigorous yet applied approach, blending theory with real-world applicability through the Kalman filter technique. Perfect for someone looking to deepen their understanding of economic and social time series models.

Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.

Forecasting, Structural Time Series Models and the Kalman Filter

Regular price
Unit price
per
Compare to estimated retail price: S$71.75  
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ISBN: 9780521405737
Authors: Andrew C. Harvey
Date of Publication: 1991-04-26
Format: Paperback
Related Collections: Economics, Science
Related Topics: Mathematics, Finance, Society
Goodreads rating: 4.18
(rated by 11 readers)

Description

This book provides a synthesis of concepts and materials that ordinarily appear separately in time series and econometrics literature, presenting a comprehensive review of both theoretical and applied concepts. Perhaps the most novel feature of the book is its use of Kalman filtering together with econometric and time series methodology. From a technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. This technique was originally developed in control engineering but is becoming increasingly important in economics and operations research. The book is primarily concerned with modeling economic and social time series and with addressing the special problems that the treatment of such series pose.
 

Advanced econometrics meets practical time series analysis.

If you've been finding traditional econometrics disconnected from practical time series analysis, Andrew Harvey's work might be the bridge you've been looking for. It dives into the complexities of forecasting with a rigorous yet applied approach, blending theory with real-world applicability through the Kalman filter technique. Perfect for someone looking to deepen their understanding of economic and social time series models.

Note: While we do our best to ensure the accuracy of cover images, ISBNs may at times be reused for different editions of the same title which may hence appear as a different cover.