Handbook of Computational Statistics: Concepts and Methods

Handbook of Computational Statistics: Concepts and Methods

Pub. Date:
Springer-Verlag New York, LLC


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Handbook of Computational Statistics: Concepts and Methods

The Handbook of Computational Statistics - Concepts and Methods is divided into 4 parts. It begins with an overview of the field of Computational Statistics, how it emerged as a seperate discipline, how it developed along the development of hard- and software, including a discussion of current active research. The second part presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for 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.

Product Details

ISBN-13: 9783540404644
Publisher: Springer-Verlag New York, LLC
Publication date: 08/26/2004
Pages: 1082
Product dimensions: 9.21(w) x 6.14(h) x 2.19(d)

Table of Contents

Part I Computational Statistics

What is Computational Statistics (James E. Gentle, Wolfgang Härdle, Yuichi Mori)

Part II Statistical Computing

Basic Computational Algorithms (John Monaham)

Random Number Generation (Pierre ĹEcuyer)

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 Günther, Joachim Lenz)

Statistical Languages (Tomoyuki Tarumi)

High-Dimensional Visualization (Edward Wegman)

Interactive Graphics (Jürgen 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 Müller)

(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 Müller)

Statistical Learning Techniques (Peter Bühlmann)

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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