ABSTRACT

Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. This second edition continues to encompass the traditional core material of computational statistics, with an

chapter Chapter 1|36 pages

Introduction

chapter Chapter 2|24 pages

Probability and Statistics Review

chapter Chapter 3|38 pages

Methods for Generating Random Variables

chapter Chapter 4|16 pages

Generating Random Processes

chapter Chapter 5|32 pages

Visualization of Multivariate Data

chapter Chapter 6|36 pages

Monte Carlo Integration and Variance Reduction

chapter Chapter 7|29 pages

Monte Carlo Methods in Inference

chapter Chapter 8|30 pages

Bootstrap and Jackknife

chapter Chapter 9|22 pages

Resampling Applications

chapter Chapter 10|32 pages

Permutation Tests

chapter Chapter 11|40 pages

Markov Chain Monte Carlo Methods

chapter Chapter 12|38 pages

Probability Density Estimation

chapter Chapter 13|26 pages

Introduction to Numerical Methods in R

chapter Chapter 14|18 pages

Optimization

chapter Chapter 15|26 pages

Programming Topics