Statistical Computing

Existing Methods and Recent Development

Debasis Kundu, Ayanendranath Basu

415 pages, parution le 03/08/2005

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Résumé

Statistical Computing: Existing Methods and Recent Developments attempts to provide a state of the art account of existing methods and recent developments in the so called new field of Statistical Computing. Fourteen different chapters deal with a wide range of topics. This includes introductory topics such as the basic numerical analysis methods, random number generation, graphical techniques used in statistical data analysis and other areas. It also covers the more specialized techniques such as the EM algorithm, genetic algorithms, nonparametric smoothing techniques, resampling methods, and artificial neural network models, to name a few. In addition, the volume also deals with the computational issues involved in the analysis of mixture models, adaptive designs, weighted distributions, and statistical signal processing, topics which are unlikely to be covered in a standard text on Statistical Computing.

L'auteur - Ayanendranath Basu

Anuradha Basu, Associate Professor, College of Business, San Jose State University

Sommaire

Basic Numerical Analysis Techniques
Generation of Random Numbers
Graphical Methods
The EM Algorithm
Genetic Algorithms for Optimization
Regression Analysis
Nonparametric Smoothing
Analysis Time Series Data
A Gentle Introduction to Resampling Plans
Neural Network Models for Regression and Classification
Statistical Computing in Mixture Models
Perspectives in Adaptive Allocation Designs: Computational Issues
Weighted Distributions
Computational Aspects in Statistical Signal Processing

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Alpha
Auteur(s)	Debasis Kundu, Ayanendranath Basu
Parution	03/08/2005
Nb. de pages	415
Format	16 x 25
Couverture	Relié
Poids	895g
Intérieur	Noir et Blanc
EAN13	9781842652022
ISBN13	978-1-84265-202-2