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Statistical Computing with R (Chapman & Hall/CRC The R Series)

Statistical Computing with R (Chapman & Hall/CRC The R Series) - Free Ebook Download

Book Detail

Author/Editor(s): Maria L. Rizzo
Publication Date: November 15, 2007
ISBN-10: 1584885459
ISBN-13: 978-1584885450
Language: English
Edition: 1
Publisher: Chapman and Hall/CRC
Size: 3.24 MB
Format: pdf

Book Description

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. Suitable for an introductory course in computational statistics or for self-study, it includes R code for all examples and R notes to help explain the R programming concepts.

After an overview of computational statistics and an introduction to the R computing environment, the book reviews some basic concepts in probability and classical statistical inference. Each subsequent chapter explores a specific topic in computational statistics. These chapters cover the simulation of random variables from probability distributions, the visualization of multivariate data, Monte Carlo integration and variance reduction methods, Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation. The final chapter presents a selection of examples that illustrate the application of numerical methods using R functions.

Focusing on implementation rather than theory, this text serves as a balanced, accessible introduction to computational statistics and statistical computing.

About the Author

Maria L. Rizzo, Bowling Green State University, Bowling Green, Ohio, U.S.A..


Practitioners in statistics need two things: Understanding of the subject and a tool to help them explore data. R is clearly the tool of choice, providing a range of capabilities. There are several introductory books on R, but none also provide the grounding in statistics that Rizzo's does. To a new student of the subject, I'd recommend this, and Gelman and Hill's DATA ANALYSIS USING REGRESSION AND MULTILEVEL/HIERARCHICAL MODELS.

--Jan Galkowski, Amazon Customer Reviews

It's a great introduction to statistical topics and computing. If you're interested in Monte Carlo Methods, this may be a good starting point. I wish I had found this book before my experience with Monte Carlo Methods.

--Public Name, Amazon Customer Reviews
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