Average Reviews:
(More customer reviews)This text is divided into three main parts: 1) Mathematical notes, 2) Theory and Methods, 3) Applications. As a reader interested in time series analysis but unfamiliar with singular spectrum analysis (SSA) per se, I was not really sure what SSA was exactly, or what it is suppose to accomplish, until nearly halfway into the book. Very early on, I found no one single sentence, paragraph, definition, or description that clearly defined SSA beyond a "technique based on spectral decomposition."
Although the text is clearly written and well organized, the authors' target audience is not well established. For example, Section I starts with an rather remedial primer on linear matrix algebra, yet Section II already seems to assume the reader has a fairly mature knowledge of statistical inference, hypothesis testing, and principal component analysis (which might be gained from courses on statistical analysis of variance, or ANOVA). The authors also make frequent references to other time series analysis techniques, such as ARMA modeling and Fourier analysis in Section III. Familiarity with ANOVA and other kinds of time series analyses will certainly benefit the reader.
One gets the impression that the manuscript has been enhanced to fill a textbook-sized volume (and would explain why the book dedicates an entire chapter to numerical examples illustrating such things as how to multiply two matrices). The font size is strikingly large for a 6" x 9" textbook, and the layout is noticeably fragmented with lots of section subtitles and large amounts of white space around these section titles. Specifically, each page accommodates no more than 34 lines of 4 1/4" wide text, which I compared with several textbooks this size which usually accommodated 40-45 lines of 4 1/2" wide text (I suspect the 153 page content might have been fitted into about 100 pages just by changing the book layout). Given the quite basic subject matter of the first few chapters, the remainder of the book is but a fairly short survey on the main subject of SSA. The advantage is that its contents can be covered relatively quickly.
The rarity of introductory texts specifically dedicated to this niche subject matter, and the uncomplicated presentation the authors have chosen, make this book a worthwhile, albeit expensive, introduction to the topic. This book has nice presentation qualities, and had it been issued as a thin, inexpensive paperback, this would more easily be a 4 or 5 star book. Similarly, this is a 4 star book for the prospective reader analyzing data related to the atmospheric sciences or climatology (as much of the authors' background materials emphasize these areas). An expanded second edition would be welcomed.
Click Here to see more reviews about: Singular Spectrum Analysis: A New Tool in Time Series Analysis
Get 20% OFF
Click here for more information about Singular Spectrum Analysis: A New Tool in Time Series Analysis
0 comments:
Post a Comment