Computational Statistics Handbook with MATLAB 1st Edition by Wendy L. Martinez, Angel R. Martinez – Ebook PDF Instant Download/Delivery: 1584882298, 978-1584882299
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Product details:
ISBN 10: 1584882298
ISBN 13: 978-1584882299
Author: Wendy L. Martinez, Angel R. Martinez
Computational Statistics Handbook with MATLAB 1st Edition: 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.
Computational Statistics Handbook with MATLAB 1st Edition Table of contents:
- Chapter 1: Introduction
- Chapter 2: Probability Concepts
- Chapter 3: Sampling Concepts
- Chapter 4: Generating Random Variables
- Chapter 5: Exploratory Data Analysis
- Chapter 6: Monte Carlo Methods for Inferential Statistics
- Chapter 7: Data Partitioning
- Chapter 8: Probability Density Estimation
- Chapter 9: Statistical Pattern Recognition
- Chapter 10: Nonparametric Regression
- Chapter 11: Markov Chain Monte Carlo Methods
- Chapter 12: Spatial Statistics
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