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				Handbook of Computational Statistics 1082 pages - hardback Springer-Verlag Berlin and Heidelberg GmbH & Co. K - (isbn 3-540-40464-3) Apr. 2004
	Price:			327,47 EUR
	Editor:			Gentle, James E. (George Mason University, USA) / Hardle, Wolfgang (Rheinische Friedrich-Wilhelms-Universitat Bonn) / Mori, Yuichi
	Description:			The "Handbook of Computational Statistics - Concepts and Methodology" ist divided into 4 parts. It begins with an overview over 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 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 focusses 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 usefullness of computational statistics.
	Contents List:			Table of Contents: 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); 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)
	Illustrations etc.:			236 illustrations
	Weight:			1633 g
	Dimensions:			230
	Publisher:			Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
				Springer-Verlag