Includes bibliographical references (pages 375-393) and index.

"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. One of the first books on these topics to feature R, Statistical Computing with R covers the traditional core material of computational statistics, with an emphasis on using the R language via an examples-based approach. It includes R code for all examples and R notes to help explain the R programming concepts." "Focusing on implementation rather than theory, this text serves as a balanced, accessible introduction to computational statistics and statistical computing."--Jacket. Probability and statistics review -- Methods for generating random variables -- Visualization of multivariate data -- Monte Carlo integration and variance reduction -- Monte Carlo methods in inference -- Bootstrap and jackknife -- Permutation tests -- Markov chain Monte Carlo methods -- Probability density estimation -- Numerical methods in R -- A. Notation -- B. Working with data frames and arrays.