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Multivariate analysis

Most popular at the top

  • An R and S-PLUS® Companion to Multivariate Analysisby Brian S. Everitt

    Springer 2006; US$ 99.00

    Most data sets collected by researchers are multivariate, and in most cases, the variables need to be examined simultaneously to get the most informative results. This book covers the core multivariate methodology along with some basic theory for each method described. It also provides the necessary R and S-PLUS code for each analysis. more...

  • Statistical Analysis of Environmental Space-Time Processesby Nhu D. Le; James V. Zidek

    Springer-Verlag New York Inc 2006; US$ 179.00

    Provides an introduction to the subject of environmental space-time processes, addressing the role of uncertainty. Within that context, this book covers a spectrum of technical matters from measurement to environmental epidemiology to risk assessment. It is suitable for statistical scientists, consultants, subject area researchers, and others. more...

  • Innovations in Classification, Data Science, and Information Systemsby Daniel Baier; Klaus-Dieter Wernecke

    Springer-Verlag Berlin and Heidelberg GmbH & Co. KG 2006; US$ 179.00

    The volume presents innovations in data analysis and classification and gives an overview of the state of the art in these scientific fields and relevant applications. Areas that receive considerable attention in the book are discrimination and clustering, data analysis and statistics, as well as applications in marketing, finance, and medicine. The... more...

  • Nonparametric Inferenceby Z Govindarajulu

    World Scientific Publishing Company 2007; US$ 236.00

    This book provides a solid foundation on nonparametric inference for students taking a graduate course in nonparametric statistics and serves as an easily accessible source for researchers in the area. With the exception of some sections requiring familiarity with measure theory, readers with an advanced calculus background will be comfortable with... more...

  • Proportional Hazards Regressionby John O'Quigley

    Springer 2008; US$ 129.00

    There are some important, significant departures from the thinking in the area of proportional hazards regression. Less weight is given to counting processes and martingale theory. This work uses classical methods of inference. more...

  • Correspondence Analysis in Practice, Second Editionby Michael Greenacre

    Taylor and Francis 2007; US$ 99.95

    Drawing on the author's experience in social and environmental research, Correspondence Analysis in Practice, Second Edition shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. This completely revised, up-to-date edition features a didactic approach with self-contained... more...

  • Semiparametric Regression for the Social Sciencesby Luke John Keele

    Wiley 2008; US$ 90.00

    An introductory guide to smoothing techniques, semiparametric estimators, and their related methods, this book describes the methodology via a selection of carefully explained examples and data sets. It also demonstrates the potential of these techniques using detailed empirical examples drawn from the social and political sciences. Each chapter includes... more...

  • Longitudinal Data Analysisby Garrett Fitzmaurice; Marie Davidian; Geert Verbeke; Geert Molenberghs

    Taylor and Francis 2008; US$ 115.95

    Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and... more...

  • Confidence Intervals in Generalized Regression Modelsby Esa Uusipaikka

    Taylor and Francis 2008; US$ 115.95

    A Cohesive Approach to Regression Models Confidence Intervals in Generalized Regression Models introduces a unified representation?the generalized regression model (GRM)?of various types of regression models. It also uses a likelihood-based approach for performing statistical inference from statistical evidence consisting of data and its statistical... more...

  • Constrained Clusteringby Sugato Basu; Ian Davidson; Kiri Wagstaff

    Taylor and Francis 2008; US$ 98.95

    Since the initial work on constrained clustering, there have been numerous advances in methods, applications, and our understanding of the theoretical properties of constraints and constrained clustering algorithms. Bringing these developments together, Constrained Clustering: Advances in Algorithms, Theory, and Applications presents an extensive... more...