Description 
1 online resource (xii, 1192 pages) 
Series 
Springer handbooks of computational statistics 

Springer handbooks of computational statistics.

Contents 
Part 1. Computational Statistics  How Computational Statistics Became the Backbone of Modern Data Science / James E. Gentle, Wolfgang Karl Härdle and Yuichi Mori  Part 2. Statistical Computing  Basic Computational Algorithms / John F. Monahan  Random Number Generation / Pierre L'Ecuyer  Markov Chain Monte Carlo Technology / Siddhartha Chib  Numerical Linear Algebra / Lenka Čížková and Pavel Čížek  The EM Algorithm / Shu Kay Ng, Thriyambakam Krishnan and Geoffrey J. McLachlan  Stochastic Optimization / James C. Spall  Transforms in Statistics / Brani Vidakovic  Parallel Computing Techniques / Junji Nakano  Statistical Databases / Claus Boyens, Oliver Günther and HansJ. Lenz  Discovering and Visualizing Relations in High Dimensional Data / Alfred Inselberg  Interactive and Dynamic Graphics / Jürgen Symanzik  The Grammar of Graphics / Leland Wilkinson  Statistical User Interfaces / Sigbert Klinke  Object Oriented Computing / Miroslav Virius  Part 3. Statistical_Methodology  Model Selection / Yuedong Wang  Bootstrap and Resampling / Enno Mammen and Swagata Nandi  Design and Analysis of Monte Carlo Experiments / Jack P.C. Kleijnen  Multivariate Density Estimation and Visualization / David W. Scott  Smoothing: Local Regression Techniques / Catherine Loader  Semiparametric Models / Joel L. Horowitz  Dimension Reduction Methods / Masahiro Mizuta  (Non) Linear Regression Modeling / Pavel Čížek  Generalized Linear Models / Marlene Müller  Robust Statistics / Laurie Davies and Ursula Gather  Bayesian Computational Methods / Christian P. Robert  Computational Methods in Survival Analysis / Toshinari Kamakura  Data and Knowledge Mining / Adalbert Wilhelm  Recursive Partitioning and Treebased Methods / Heping Zhang  Support Vector Machines / Konrad Rieck, Sören Sonnenburg, Sebastian Mika, Christin Schäfer and Pavel Laskov, et al.  Learning Under Nonstationarity: Covariate Shift Adaptation by Importance Weighting / Masashi Sugiyama  Saddlepoint Approximations: A Review and Some New Applications / Simon A. Broda and Marc S. Paolella  Bagging, Boosting and Ensemble Methods / Peter Bühlmann  Part 4. Selected Applications  HeavyTailed Distributions in VaR Calculations / Adam Misiorek and Rafał Weron  Econometrics / Luc Bauwens and Jeroen V.K. Rombouts  Statistical and Computational Geometry of Biomolecular Structure / Iosif I. Vaisman  Functional Magnetic Resonance Imaging / William F. Eddy and Rebecca L. McNamee  Network Intrusion Detection / David J. Marchette 
Summary 
The Handbook of Computational Statistics  Concepts and Methods (second edition) is a revision of the first edition published in 2004, and contains additional comments and updated information on the existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. ¡ This new edition is divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2  15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, highdimensional data and graphics treatment are discussed. The third part (Chs. 16  33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34  38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in realworld applications 
Analysis 
Statistics 

Mathematical statistics 

Statistics and Computing/Statistics Programs 

Statistical Theory and Methods 
Bibliography 
Includes bibliographical references and index 
Subject 
Mathematical statistics  Data processing  Handbooks, manuals, etc.


Statistics as Topic.

Genre/Form 
Handbook.


Handbooks and manuals.


Handbooks and manuals.

Form 
Electronic book

Author 
Gentle, James E., 1943


Härdle, Wolfgang.


Mori, Yuichi.

ISBN 
3642215513 (electronic bk.) 

9783642215513 (electronic bk.) 
