Handbook of computational statistics : concepts and methods
著者
書誌事項
Handbook of computational statistics : concepts and methods
Springer, c2004
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
The Handbook of Computational Statistics: Concepts and Methodology is divided into four parts. It begins with an overview over the field of Computational Statistics. The second part presents several topics in the supporting field of statistical computing. Emphasis is placed on the need of fast and accurate numerical algorithms and it discusses some of the basic methodologies for transformation, data base handling and graphics treatment. The third part focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Finally a set of selected applications like Bioinformatics, Medical Imaging, Finance and Network Intrusion Detection highlight the usefulness of computational statistics.
目次
Part I Computational Statistics What is Computational Statistics (James E. Gentle, Wolfgang Hardle, Yuichi Mori) Part II Statistical Computing Basic Computational Algorithms (John Monaham) Random Number Generation (Pierre L'Ecuyer) MCMC Technology (Siddartha Chib) Numerical Linear Algebra (Lenka Cizkova) The EM Algorithm (Geoffrey McLachlan) Stochastic Optimization (James C. Spall) Transforms (Brani Vidakovic) Parallel Computing Techniques (Junji Nakano) Data Base Methodology (Oliver Gunther, Joachim Lenz) Statistical Languages (Tomoyuki Tarumi) High-Dimensional Visualization (Edward Wegman) Interactive Graphics (Jurgen Symanzik) The Grammar of Graphics (Leland Wilkinson) User Interfaces (Sigbert Klinke) Object Oriented Computing (Miroslav Virius) Part III Statistical Methodology Cross Validation and Model Choice (Yuedong Wang) Bootstrap and Resampling (Enno Mammen) Simulation Techniques (Jack Kleijnen) Multivariate Density Estimation and Visualization (David Scott) Smoothing: Local Regression Techniques (Catherine Loader) Dimension Reduction Methods (Masahiro Mizuta) Generalized Linear Models (Marlene Muller) (Non) linear Regression Modelling (Pavel Cizek) Robustness Issues (P. Laurie Davies, Ursula Gather) Semiparametrics (Joel Horowitz) Computational Methods in Bayesian Analysis (Christian Robert) Data and Knowledge Mining (Adalbert X. Wilhelm) Tree Based Methods (Heping Zhang) Neural Networks (nn) Support Vector Machines (Klaus-Robert Muller) Statistical Learning Techniques (Peter Buhlmann) Computational Methods in Survival Analysis ( Toshinari Kamakura) Part IV Selected Applications Finance (Rafal Weron) Econometrics (Luc Bauwens) Bioinformatics (Iosif Vaisman) Functional MRI (William F. Eddy) Network Intrusion Detection (David Marchette)
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