Computational Statistics Handbook with MATLAB

ISBN-10: 1584882298
ISBN-13: 9781584882299
Edition: 2002
List price: $104.95
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Description: 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  More...

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Book details

List price: $104.95
Copyright year: 2002
Publisher: CRC Press LLC
Publication date: 9/26/2001
Binding: Hardcover
Pages: 616
Size: 6.50" wide x 9.25" long x 1.50" tall
Weight: 2.134
Language: English

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.

Preface
Introduction
What Is Computational Statistics?
An Overview of the Book
Matlab Code
Further Reading
Probability Concepts
Introduction
Probability
Conditional Probability and Independence
Expectation
Common Distributions
Matlab Code
Further Reading
Exercises
Sampling Concepts
Introduction
Sampling Terminology and Concepts
Sampling Distributions
Parameter Estimation
Empirical Distribution Function
Matlab Code
Further Reading
Exercises
Generating Random Variables
Introduction
General Techniques for Generating Random Variables
Generating Continuous Random Variables
Generating Discrete Random Variables
Matlab Code
Further Reading
Exercises
Exploratory Data Analysis
Introduction
Exploring Univariate Data
Exploring Bivariate and Trivariate Data
Exploring Multi-Dimensional Data
Matlab Code
Further Reading
Exercises
Monte Carlo Methods for Inferential Statistics
Introduction
Classical Inferential Statistics
Monte Carlo Methods for Inferential Statistics
Bootstrap Methods
Matlab Code
Further Reading
Exercises
Data Partitioning
Introduction
Cross-Validation
Jackknife
Better Bootstrap Confidence Intervals
Jackknife-After-Bootstrap
Matlab Code
Further Reading
Exercises
Probability Density Estimation
Introduction
Histograms
Kernel Density Estimation
Finite Mixtures
Generating Random Variables
Matlab Code
Further Reading
Exercises
Statistical Pattern Recognition
Introduction
Bayes Decision Theory
Evaluating the Classifier
Classification Trees
Clustering
Matlab Code
Further Reading
Exercises
Nonparametric Regression
Introduction
Smoothing
Kernel Methods
Regression Trees
Matlab Code
Further Reading
Exercises
Markov Chain Monte Carlo Methods
Introduction
Background
Metropolis-Hastings Algorithms
The Gibbs Sampler
Convergence Monitoring
Matlab Code
Further Reading
Exercises
Spatial Statistics
Introduction
Visualizing Spatial Point Processes
Exploring First-order and Second-order Properties
Modeling Spatial Point Processes
Simulating Spatial Point Processes
Matlab Code
Further Reading
Exercises
Introduction to Matlab
What Is Matlab?
Getting Help in Matlab
File and Workspace Management
Punctuation in Matlab
Arithmetic Operators
Data Constructs in Matlab
Script Files and Functions
Control Flow
Simple Plotting
Contact Information
Index of Notation
Projection Pursuit Indexes
Indexes
Matlab Source Code
Matlab Code
Bootstrap Confidence Interval
Adaptive Mixtures Density Estimation
Classification Trees
Regression Trees
Matlab Statistics Toolbox
Computational Statistics Toolbox
Data Sets
References
Index

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