"All topics are well illustrated with good examples from a fairlywide range of applications... the book's usefulness isenhanced by a glossary of multiway terminology, a good index andreferences to extension work... this is a well-crafted and highlyreadable book.„ (Journal of the Royal Statistical Society-Series A, 2009)
“All in all, Kroonenberg's book constitutes anextremely valuable tool for applied researchers in almost alldomains of investigation, whenever they are faced with the task ofanalyzing complex statistical data in view of obtaining usefulinformation in their areas of interest.„ (Biometrics, June 2009)
“This book is focused primarily toward graduate studentsin the areas of chemistry, social and behavioral sciences, andenvironmental sciences, although the techniques and methods usedcan be more broadly used in other areas, such as finance andengineering, as well.„ (Technometrics, May 2009)
“Kroonenberg's book constitutes an extremely valuable toolfor applied researchers in almost all domains of investigation(from economics to psychology, from biomedicine to technology andphysical sciences), whenever they are faced with the task ofanalyzing complex statistical data in view of obtaining usefulinformation in their areas of interest.„(Biometrics 2009)
“... the combination of worked-out examples alongsidedescriptions and critical considerations on the theory behind thoseanalyses make AMDA an interesting book for researchers andpractitioners in both academia and industry. (Journal of theAmerican Statistical Association 2009)
"The book is written in a clear style and mostly in conceptualrather than mathematical level. It emphasized the author's overthirty years' personal experience and practical side of performingmultiway data analyses. It is easy to recommend this book, as itreally open news views of the world.„ (International StatisticalReview, December 2008)
“Good things take time - and this hold for this book aswell... Pieter Kroonenberg is one of the few with a profoundknowledge of multiway analysis. It is meritorious that he took theeffort to share his knowledge. It is to be hoped that a nextedition will appear soon... the book deserves a broad readingpublic.„ (Vereniging voor Ordinatie en Classificatie, Nieuwsbrief, no 41, November 2008)
“We believe that this book will offer applied researchers a lotof good advice for using three-way techniques. In addition, Applied Multiway Data-Analysis will turn out to be avaluable resource of reference for three-way specialists."(Mathematical Reviews, 2008)
Applied Multiway Data Analysis
von P. M. KroonenbergThis groundbreaking book is the first of its kind to presentmethods for analyzing multiway data by applying multiway componenttechniques. Multiway analysis is a specialized branch of the largerfield of multivariate statistics that extends the standard methodsfor two-way data, such as component analysis, factor analysis, cluster analysis, correspondence analysis, and multidimensionalscaling to multiway data. Applied Multiway Data Analysis presents aunique, thorough, and authoritative treatment of this relativelynew and emerging approach to data analysis that is applicableacross a range of fields, from the social and behavioral sciencesto agriculture, environmental sciences, and chemistry.
General introductions to multiway data types, methods, andestimation procedures are provided in addition to detailedexplanations and advice for readers who would like to learn moreabout applying multiway methods. Using carefully laid out examplesand engaging applications, the book begins with an introductorychapter that serves as a general overview of multiway analysis, including the types of problems it can address. Next, the processof setting up, carrying out, and evaluating multiway analyses isdiscussed along with commonly encountered issues, such aspreprocessing, missing data, model and dimensionality selection, postprocessing, and transformation, as well as robustness andstability issues.
Extensive examples are presented within a unified frameworkconsisting of a five-step structure: objectives; data descriptionand design; model and dimensionality selection; results and theirinterpretation; and validation. Procedures featured in the book areconducted using 3WayPack, which is software developed by theauthor, and analyses can also be carried out within the R andMATLAB systems. Several data sets and 3WayPack can be downloadedvia the book's related Web site.
The author presents the material in a clear, accessible stylewithout unnecessary or complex formalism, assuring a smoothtransition from well-known standard two-analysis to multiwayanalysis for readers from a wide range of backgrounds. Anunderstanding of linear algebra, statistics, and principalcomponent analyses and related techniques is assumed, though theauthor makes an effort to keep the presentation at a conceptual, rather than mathematical, level wherever possible. Applied MultiwayData Analysis is an excellent supplement for component analysis andstatistical multivariate analysis courses at theupper-undergraduate and beginning graduate levels. The book canalso serve as a primary reference for statisticians, data analysts, methodologists, applied mathematicians, and social scienceresearchers working in academia or industry.
Visit the Related Website: http://three-mode. leidenuniv. nl/, to view data from the book.
