MARC details
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
100227s2008 000 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
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| LC control number |
2007034218 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781584885450 (alk. paper) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
1584885459 (alk. paper) |
| 035 ## - SYSTEM CONTROL NUMBER |
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| System control number |
(Sirsi) u3886 |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
EG-CaNU |
| -- |
EG-CaNU |
| -- |
EG-CaNU |
| 042 ## - AUTHENTICATION CODE |
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| Authentication code |
ncode |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
519.502855133 |
| Edition number |
22 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Rizzo, Maria L. |
| 9 (RLIN) |
4470 |
| 245 10 - TITLE STATEMENT |
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| Title |
Statistical computing with R / |
| Statement of responsibility, etc. |
Maria L. Rizzo. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Boca Raton : |
| Name of publisher, distributor, etc. |
Chapman & Hall/CRC, |
| Date of publication, distribution, etc. |
c2008. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvi, 399 p. : |
| Other physical details |
ill. ; |
| Dimensions |
25 cm. |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Chapman & Hall/CRC computer science and data analysis series |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references (p. 375-393) and index. |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Prefacep. xv Introductionp. 1 Computational Statistics and Statistical Computingp. 1 The R Environmentp. 3 Getting Started with Rp. 4 Using the R Online Help Systemp. 7 Functionsp. 8 Arrays, Data Frames, and Listsp. 9 Workspace and Filesp. 15 Using Scriptsp. 17 Using Packagesp. 18 Graphicsp. 19 Probability and Statistics Reviewp. 21 Random Variables and Probabilityp. 21 Some Discrete Distributionsp. 25 Some Continuous Distributionsp. 29 Multivariate Normal Distributionp. 33 Limit Theoremsp. 35 Statisticsp. 35 Bayes' Theorem and Bayesian Statisticsp. 40 Markov Chainsp. 42 Methods for Generating Random Variablesp. 47 Introductionp. 47 The Inverse Transform Methodp. 49 The Acceptance-Rejection Methodp. 55 Transformation Methodsp. 58 Sums and Mixturesp. 61 Multivariate Distributionsp. 69 Stochastic Processesp. 82 Exercisesp. 94 Visualization of Multivariate Datap. 97 Introductionp. 97 Panel Displaysp. 97 Surface Plots and 3D Scatter Plotsp. 100 Contour Plotsp. 106 Other 2D Representations of Datap. 110 Other Approaches to Data Visualizationp. 115 Exercisesp. 116 Monte Carlo Integration and Variance Reductionp. 119 Introductionp. 119 Monte Carlo Integrationp. 119 Variance Reductionp. 126 Antithetic Variablesp. 128 Control Variatesp. 132 Importance Samplingp. 139 Stratified Samplingp. 144 Stratified Importance Samplingp. 147 Exercisesp. 149 R Codep. 152 Monte Carlo Methods in Inferencep. 153 Introductionp. 153 Monte Carlo Methods for Estimationp. 154 Monte Carlo Methods for Hypothesis Testsp. 162 Applicationp. 174 Exercisesp. 180 Bootstrap and Jackknifep. 183 The Bootstrapp. 183 The Jackknifep. 190 Jackknife-after-Bootstrapp. 195 Bootstrap Confidence Intervalsp. 197 Better Bootstrap Confidence Intervalsp. 203 Applicationp. 207 Exercisesp. 212 Permutation Testsp. 215 Introductionp. 215 Tests for Equal Distributionsp. 219 Multivariate Tests for Equal Distributionsp. 222 Applicationp. 235 Exercisesp. 242 Markov Chain Monte Carlo Methodsp. 245 Introductionp. 245 The Metropolis-Hastings Algorithmp. 247 The Gibbs Samplerp. 263 Monitoring Convergencep. 266 Applicationp. 271 Exercisesp. 277 R Codep. 279 Probability Density Estimationp. 281 Univariate Density Estimationp. 281 Kernel Density Estimationp. 296 Bivariate and Multivariate Density Estimationp. 305 Other Methods of Density Estimationp. 314 Exercisesp. 314 R Codep. 317 Numerical Methods in Rp. 319 Introductionp. 319 Root-finding in One Dimensionp. 326 Numerical Integrationp. 330 Maximum Likelihood Problemsp. 335 One-dimensional Optimizationp. 338 Two-dimensional Optimizationp. 342 The EM Algorithmp. 345 Linear Programming - The Simplex Methodp. 348 Applicationp. 349 Exercisesp. 353 Notationp. 355 Working with Data Frames and Arraysp. 357 Resampling and Data Partitioningp. 357 Subsetting and Reshaping Datap. 360 Data Entry and Data Analysisp. 364 Referencesp. 375 Indexp. 395 Table of Contents provided by Ingram. All Rights Reserved. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
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. |
| 596 ## - |
|---|
| -- |
1 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Mathematical statistics |
| General subdivision |
Data processing. |
| 9 (RLIN) |
7656 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Statistics |
| General subdivision |
Data processing. |
| 9 (RLIN) |
7657 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
R (Computer program language) |
| 9 (RLIN) |
2301 |