9780199228874-0199228876-An Introduction to State Space Time Series Analysis (Practical Econometrics)

An Introduction to State Space Time Series Analysis (Practical Econometrics)

ISBN-13: 9780199228874
ISBN-10: 0199228876
Edition: 1
Author: Siem Jan Koopman, Jacques J.F. Commandeur
Publication date: 2007
Publisher: Oxford University Press
Format: Hardcover 192 pages
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Book details

ISBN-13: 9780199228874
ISBN-10: 0199228876
Edition: 1
Author: Siem Jan Koopman, Jacques J.F. Commandeur
Publication date: 2007
Publisher: Oxford University Press
Format: Hardcover 192 pages

Summary

An Introduction to State Space Time Series Analysis (Practical Econometrics) (ISBN-13: 9780199228874 and ISBN-10: 0199228876), written by authors Siem Jan Koopman, Jacques J.F. Commandeur, was published by Oxford University Press in 2007. With an overall rating of 3.7 stars, it's a notable title among other Econometrics & Statistics (Economics) books. You can easily purchase or rent An Introduction to State Space Time Series Analysis (Practical Econometrics) (Hardcover) from BooksRun, along with many other new and used Econometrics & Statistics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $2.85.

Description

Providing a practical introduction to state space methods as applied to unobserved components time series models, also known as structural time series models, this book introduces time series analysis using state space methodology to readers who are neither familiar with time series analysis, nor with state space methods. The only background required in order to understand the material presented in the book is a basic knowledge of classical linear regression models, of which brief review is provided to refresh the reader's knowledge. Also, a few sections assume familiarity with matrix algebra, however, these sections may be skipped without losing the flow of the exposition.

The book offers a step by step approach to the analysis of the salient features in time series such as the trend, seasonal, and irregular components. Practical problems such as forecasting and missing values are treated in some detail. This useful book will appeal to practitioners and researchers who use time series on a daily basis in areas such as the social sciences, quantitative history, biology and medicine. It also serves as an accompanying textbook for a basic time series course in econometrics and statistics, typically at an advanced undergraduate level or graduate level.

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