Page 8 - Jolliffe I. Principal Component Analysis

Preface to the Second Edition
vii
tichannel) singular spectrum analysis, complex PCA, principal oscillation
pattern analysis, and extended empirical orthogonal functions (EOFs).
Many of these techniques were developed by atmospheric scientists and
are little known in many other disciplines.
The last two chapters of the first edition are greatly expanded and be-
come Chapters 13 and 14 in the new edition. There is some transfer of
material elsewhere, but also new sections. In Chapter 13 there are three
new sections, on size/shape data, on quality control and a final ‘odds-and-
ends’ section, which includes vector, directional and complex data, interval
data, species abundance data and large data sets. All other sections have
been expanded, that on common principal component analysis and related
topics especially so.
The first section of Chapter 14 deals with varieties of non-linear PCA.
This section has grown substantially compared to its counterpart (Sec-
tion 12.2) in the first edition. It includes material on the Gifi system of
multivariate analysis, principal curves, and neural networks. Section 14.2
on weights, metrics and centerings combines, and considerably expands,
the material of the first and third sections of the old Chapter 12. The
content of the old Section 12.4 has been transferred to an earlier part in
the book (Chapter 10), but the remaining old sections survive and are
updated. The section on non-normal data includes independent compo-
nent analysis (ICA), and the section on three-mode analysis also discusses
techniques for three or more groups of variables. The penultimate section
is new and contains material on sweep-out components, extended com-
ponents, subjective components, goodness-of-fit, and further discussion of
neural nets.
The appendix on numerical computation of PCs has been retained
and updated, but, the appendix on PCA in computer packages has
been dropped from this edition mainly because such material becomes
out-of-date very rapidly.
The preface to the first edition noted three general texts on multivariate
analysis. Since 1986 a number of excellent multivariate texts have appeared,
including Everitt and Dunn (2001), Krzanowski (2000), Krzanowski and
Marriott (1994) and Rencher (1995, 1998), to name just a few. Two large
specialist texts on principal component analysis have also been published.
Jackson (1991) gives a good, comprehensive, coverage of principal com-
ponent analysis from a somewhat different perspective than the present
book, although it, too, is aimed at a general audience of statisticians and
users of PCA. The other text, by Preisendorfer and Mobley (1988), con-
centrates on meteorology and oceanography. Because of this, the notation
in Preisendorfer and Mobley differs considerably from that used in main-
stream statistical sources. Nevertheless, as we shall see in later chapters,
especially Chapter 12, atmospheric science is a field where much devel-
opment of PCA and related topics has occurred, and Preisendorfer and
Mobley’s book brings together a great deal of relevant material.