This book is concerned with data in which the observations are
independent and in which the response is multivariate. Anthony
Atkinson has been Professor of Statistics at the London School of
Economics since 1989. Before that he was a Professor at Imperial
College, London. He is the author of Plots, Transformations, and
Regression, co-author of Optimum Experimental Designs, and joint
editor of The Fascination of Statistics, a volume celebrating the
centenary of the International Statistical Institute. Professor
Atkinson has served as editor of The Journal of the Royal
Statistical Society, Series B and as associate editor of Biometrika
and Technometrics. He has published well over 100 articles in these
and other journals including The Annals of Statistics, Biometrics,
The Journal of the American Statistical Association, and Statistics
and Computing. Marco Riani, after receiving his Ph.D. in Statistics
in 1995 from the University of Florence, joined the Faculty of
Economics at Parma University as postdoctoral fellow. In 1997 he
won the prize for the best Italian Ph.D. thesis in Statistics. He
is currently Associate Professor of Statistics in the University of
Parma. He has published in Technometrics, The Journal of
Computational and Graphical Statistics, The Journal of Business and
Economic Statistics, The Journal of Forecasting, Environmetrics,
Computational Statistics and Data Analysis, Metron, and other
journals.
From the reviews:
"The book requires knowledge of multivariate statistical
methods, because it provides only basic background information on
the methods considered (although with excellent references for
futher reading at the end of each chapter). Each chapter
alsoincludes exercises with solutions...This book could serve as an
excellent text for an advanced course on modern multivariate
statistics, as it is intended." Technometrics, November 2004
"This book is full of interest for anyone undertaking
multivariate analyses, clearly emphasizing that uncritical use of
standard methods can be misleading." Short Book Reviews of the
International Statistical Institute, December 2004
"This book is an interesting complement to various textbooks on
multivariate statistics." Biometrics, December 2005
"This book discusses multivariate data from a different
perspective. a ] it is an excellent book for researchers with
interests in multivariate data and cluster analysis. It may also be
a good reference for students of advanced statistics and
practitioners working with large volumes of data a ] ." (Kassim S.
Mwitondi, Journal of Applied Statistics, Vol. 32 (4), 2005)
"This is a companion to an earlier book a ] both of which
feature many informative graphs. Here, the forward search has been
applied in detail to classical multivariate approaches used with
Gaussian data. a ] One valuable feature of the book is the way that
the illustrations concentrate on a relatively small number a ] .
This makes it easy to concentrate on the application a ] . The
implications of this book also strengthen the importance of data
visualization, as well as providing a valuable approach to
visualization." (Paul Hewson, Journal of the Royal Statistical
Society Series A, Vol. 168 (2), 2005)
"This book is a companion to Atkinson a ] . The objective is to
identify outliers, appreciate their influence a ] which would
result in an overall improvement. a ] Graphical tools arewidely
used, resulting in three hundred and ninety figures. Each chapter
is followed by extensive exercises and their solutions, and the
book could be used as an advanced textbook for multivariate
analysis courses. Web-sites provide the relevant software a ] .
This book is full of interest for anyone undertaking multivariate
analyses a ] ." (B.J.T. Morgan, Short Book Reviews International
Statistical Institute, Vol. 24 (3), 2004)
"This book discusses forward search (FS), a method using graphs
to explore and model continuous multivariate data a ] . Its
viewpoint is toward applications, and it demonstrates the merits of
FS using a variety of examples, with a thorough discussion of
statistical issues and interpretation of results. a ] This book
could serve as an excellent text for an advanced course on modern
multivariate statistics, as it is intended." (Tena Ipsilantis
Katsaounis, Technometrics, Vol. 46 (4), November, 2004)
"The theoretical exercises with detailed solutions at the end of
each chapter are extremely useful. I would recommend this book to
practitioners who analyze moderately sized multivariate data. Of
course, anyone associated with the application of statistics should
find the book interesting to read." (Tathgata Banerjee, Journal of
the American Statistical Association, March 2006)
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