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 a 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.
The book was published on July 19, 2007, by Oxford University Press (OUP).
Interested readers can download all the Ox code and data sets in zip format for performing the analyses presented in the book simultaneously here:
All chapters.
Alternatively, you can separately download the Ox code and corresponding data set(s) in zip format chapter by chapter here:
| Chapter 1 | Introduction |
| Chapter 2 | The Local Level Model |
| Chapter 3 | The Local Linear Trend Model |
| Chapter 4 | The Local Level Model with Seasonal |
| Chapter 5 | The Local Level Model with Explanatory Variable |
| Chapter 6 | The Local Level Model with Intervention Variable |
| Chapter 7 | The UK Seat Belt and Inflation Models |
| Chapter 8 | General Treatment of Univariate State Space Models |
| Chapter 9 | Multivariate Time Series Analysis |
| Chapter 10 | State Space and Box-Jenkins Methods for Time Series Analysis |
| Chapter 11 | State Space Modelling in Practice |
SsfPack version 3.0 is needed to run all of this Ox code.
These are quotes from the first review by T. Sabin on Amazon:
“This is the book that I wish was available when I first began using state space time series models ...”
“Overall, if you would like to understand state space time series analysis and like learning by example then this is a good place to start.”
These are quotes from the second review by Roy Marsten on Amazon:
“I found this book extremely helpful and I highly recommend it ...”
“I have read the classics: Harvey (1989) and Durbin and Koopman (2002) and they are great, but they leave out all the practical stuff. ... How do we actually use this stuff? That is where Commandeur & Koopman is invaluable.”
This is the first official review of the book by dr. P.H.C. (Paul) Eilers as it appeared in the March 2008 Newsletter of the Dutch Classification Society.
A list of corrections and additions to the book can be downloaded here in pdf format.
An Introduction to State Space Time Series Analysis by Jacques J.F. Commandeur and Siem Jan Koopman was published as volume 1 in the Practical Econometrics series by Oxford University Press, and can be ordered from OUP-UK (where a sample of the book can be downloaded for free: Chapter 1, the introduction to the book), OUP-US, and Amazon, amongst others.
