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Multiple comparisons (Statistics)

  • Ensemble Methodsby Zhi-Hua Zhou

    Taylor and Francis 2012; US$ 83.95

    An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After presenting background and terminology, the book... more...

  • Probabilistic Databasesby Dan Suciu; Dan Olteanu; Christop Koch; Christoph Koch

    Morgan & Claypool Publishers 2011; US$ 45.00

    Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of uncertain... more...

  • Multiple Comparisons Using Rby Frank Bretz; Torsten Hothorn; Peter Westfall

    Taylor and Francis 2010; US$ 91.95

    Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code for the analyses are available at http://CRAN.R-project.org... more...

  • Applied Multiway Data Analysisby Pieter M. Kroonenberg

    Wiley 2008; US$ 159.00

    From a preeminent authority—a modern and applied treatment of multiway data analysis This groundbreaking book is the first of its kind to present methods for analyzing multiway data by applying multiway component techniques. Multiway analysis is a specialized branch of the larger field of multivariate statistics that extends the standard methods... more...

  • Multilevel Modelingby Steven P. Reise; Naihua Duan

    Taylor and Francis 2003; US$ 52.95

    This book illustrates the current work of leading multilevel modeling (MLM) researchers from around the world. The book's goal is to critically examine the real problems that occur when trying to use MLMs in applied research, such as power, experimental design, and model violations. This presentation of cutting-edge work and statistical innovations... more...

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