Computational statistics handbook with Matlab

Wendy L Martinez, Angel R Martinez

592 pages, parution le 06/11/2001

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Résumé

Approaching computational statistics through its theoretical aspects can be daunting. Often intimidated or distracted by the theory, researchers and students can lose sight of the actual goals and applications of the subject. What they need are its key concepts, an understanding of its methods, experience with its implementation, and practice with computational software.Focusing on the computational aspects of statistics rather than the theoretical, Computational Statistics Handbook with MATLAB uses a down-to-earth approach that makes statistics accessible to a wide range of users. The authors integrate the use of MATLAB throughout the book, allowing readers to see the actual implementation of algorithms, but also include step-by-step procedures to allow implementation with any suitable software.

The book concentrates on the simulation/Monte Carlo point of view, and contains algorithms for exploratory data analysis, modeling, Monte Carlo simulation, pattern recognition, bootstrap, classification, cross-validation methods, probability density estimation, random number generation, and other computational statistics methods.Emphasis on the practical aspects of statistics, details of the latest techniques, and real implementation experience make the Computational Statistics Handbook with MATLAB more than just the first book to use MATLAB to solve computational problems in statistics. It also forms an outstanding, introduction to statistics for anyone in the many disciplines that involve data analysis.

Focuses on implementation and explains theory in lay terms
Provides detailed algorithms and MATLAB code for the methods presented
Includes a Computational Statistics Toolbox for MATLAB
Recommends sources for learning the theory behind the methods
Includes exercises at the end of each chapter
Contains a brief introduction to MATLAB for those unfamiliar with it

Table of Contents

Preface
Ch. 1 Introduction
Ch. 2 Probability Concepts
Ch. 3 Sampling Concepts
Ch. 4 Generating Random Variables
Ch. 5 Exploratory Data Analysis
Ch. 6 Monte Carlo Methods for Inferential Statistics
Ch. 7 Data Partitioning
Ch. 8 Probability Density Estimation
Ch. 9 Statistical Pattern Recognition
Ch. 10 Nonparametric Regression
Ch. 11 Markov Chain Monte Carlo Methods
Ch. 12 Spatial Statistics
App. A Introduction to Matlab
App. B: Index of Notation
App. C Projection Pursuit Indexes
App. D Matlab Code
App. E Matlab Statistics Toolbox
App. F Computational Statistics Toolbox
App. G: Data Sets
References
Index

Caractéristiques techniques

	PAPIER
Éditeur(s)	CRC Press (Taylor and Francis Group)
Auteur(s)	Wendy L Martinez, Angel R Martinez
Parution	06/11/2001
Nb. de pages	592
Format	16 x 24,2
Couverture	Relié
Poids	972g
Intérieur	Noir et Blanc
EAN13	9781584882299
ISBN13	978-1-58488-229-9