Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series)

You looking to find the "Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series)" Good news! You can purchase Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series) with secure price and compare to view update price on this product. And deals on this product is available only for limited time.

   

Product Description

This new edition updates Durbin & Koopman's important text on the state space approach to time series analysis. The distinguishing feature of state space time series models is that observations are regarded as made up of distinct components such as trend, seasonal, regression elements and disturbance terms, each of which is modelled separately. The techniques that emerge from this approach are very flexible and are capable of handling a much wider range of problems than the
main analytical system currently in use for time series analysis, the Box-Jenkins ARIMA system. Additions to this second edition include the filtering of nonlinear and non-Gaussian series.

Part I of the book obtains the mean and variance of the state, of a variable intended to measure the effect of an interaction and of regression coefficients, in terms of the observations.

Part II extends the treatment to nonlinear and non-normal models. For these, analytical solutions are not available so methods are based on simulation.

Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series) Review

"Preface to Second Edition", found via "Search inside", discusses the changes since the first edition, and these do address readers' comments on that book's Amazon page, by expanding coverage of the non-linear/non-normal case. I must say the book still feels like one about Kalman filter, but page-count comparisons* I now invoke to justify this feeling may be misleading. "Time series analysis by state space methods" was not quite what I was looking for - I'd prefer something less dry/technical, and more application-minded and hands-on (regrettably, readers' complaints regarding companion software have not been heeded; this, and the book's steep price, are my excuse not to give it five stars) - and I did not dig deep, but the overall impression is that of a comprehensive, rigorous and reasonably compact exploration of the field.

* The "non-linear/non-normal" Part II has half as many pages as the "linear/normal" Part I; linearity gains extra ground in Part II's chapter on approximate methods (including extended and unscented Kalman filer), and leaves less space for particle filtering. The latter gets a total of 23 pages; I opted to read the survey paper by Drew Creal, available online, and to revisit the concluding chapter of "Dynamic linear models with R" by Petris et al.

Most of the consumer Reviews tell that the "Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series)" are high quality item. You can read each testimony from consumers to find out cons and pros from Time Series Analysis by State Space Methods: Second Edition (Oxford Statistical Science Series) ...