ABSTRACT

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

chapter 1|10 pages

Introduction

chapter 2|40 pages

Probability Concepts

chapter 3|28 pages

Sampling Concepts

chapter 4|32 pages

Generating Random Variables

chapter 5|80 pages

Exploratory Data Analysis

chapter 7|28 pages

Data Partitioning

chapter 8|58 pages

Probability Density Estimation

chapter 9|68 pages

Statistical Pattern Recognition

chapter 10|40 pages

Nonparametric Regression

chapter 11|40 pages

Markov Chain Monte Carlo Methods

chapter 12|46 pages

Spatial Statistics