Uncertainty Analysis With High Dimensional Dependence Modelling

of it means — however, if the reader has previously failed to understand these terms, I doubt that the discussion will help. It may help newcomers. On the other hand, some things are misstated here including “[t]he closer to ±1, the closer to a perfect linear relationship.” However, it is easy to obtain a high correlation (over .8) with a nonlinear relationship (Anscombe 1973; Analytical Methods Committee 1988). Finally, Chapter 7 provides help on searching for information. Each chapter ends with an “on your own” section of exercises—I found many of these confusing. The author’s website for this book, checked on 10/11/06, is still in the very early stages; most of the material was written before the book. There is no section on correction of errors. The author states that “I plan to add resources when I have time, such as answers to On your Own exercises and a bibliography with live links to the free full text when available.” Notwithstanding my negative comments and tone above, there are valuable points here; they are, however, generally too hard to find and some of them are undercut by the author’s misguided attempt to be “fair.” If the author were to clean up the typographical errors and omissions and highlight the main points, the result would be a much better book.