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# Computational Statistics with R

- 1st Edition, Volume 32 - November 25, 2014
- Editors: Marepalli B. Rao, C.R. Rao
- Language: English
- Hardback ISBN:9 7 8 - 0 - 4 4 4 - 6 3 4 3 1 - 3
- eBook ISBN:9 7 8 - 0 - 4 4 4 - 6 3 4 4 1 - 2

R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation al… Read more

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## Institutional subscription on ScienceDirect

Request a sales quoteR is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily high quality. R was recently ranked in 14th place by the Transparent Language Popularity Index and 6th as a scripting language, after PHP, Python, and Perl.

The book is designed so that it can be used right away by novices while appealing to experienced users as well. Each article begins with a data example that can be downloaded directly from the R website. Data analysis questions are articulated following the presentation of the data. The necessary R commands are spelled out and executed and the output is presented and discussed. Other examples of data sets with a different flavor and different set of commands but following the theme of the article are presented as well. Each chapter predents a hands-on-experience. R has superb graphical outlays and the book brings out the essentials in this arena. The end user can benefit immensely by applying the graphics to enhance research findings. The core statistical methodologies such as regression, survival analysis, and discrete data are all covered.

- Addresses data examples that can be downloaded directly from the R website
- No other source is needed to gain practical experience
- Focus on the essentials in graphical outlays

Teachers of statistics, students, statistical consultants, statisticians and biostatisticians in industry

- Preface
- Chapter 1: Introduction to R
- Chapter 2: R Graphics
- Chapter 3: Graphics Miscellanea
- Chapter 4: Matrix Algebra Topics in Statistics and Economics Using R
- Chapter 5: Sample Size Calculations with R: Level 1
- Chapter 6: Sample Size Calculations with R: Level 2
- Chapter 7: Binomial Regression in R
- Chapter 8: Computing Tolerance Intervals and Regions Using R
- Chapter 9: Modeling the Probability of Second Cancer in Controlled Clinical Trials
- Chapter 10: Bayesian Networks

- Chapter 1: Introduction to R
- Abstract
- 1 Introduction
- 2 Setting Up R
- 3 Basic R Objects and Commands
- 4 Writing Programs
- 5 Input and Output
- 6 Data Processing
- 7 Exploratory Data Analysis
- 8 Statistical Inference and Modeling
- 9 Simulation
- 10 Numerical Techniques
- 11 Annotated References

- Chapter 2: R Graphics
- Abstract
- 1 Introduction
- 2 Traditional Graphics
- 3 Grid Graphics
- 4 Lattice
- 5 ggplot
- 6 Further Reading

- Chapter 3: Graphics Miscellanea
- Abstract
- 1 Introduction
- 2 The
*Plot()*Command - 3 Scatter Plots
- 4 Time Series Plots
- 5 Pie Charts
- 6 Special Box Plots
- 7
*xy*Plots - 8 Curves
- 9 LOWESS
- 10 Sunflower Plots
- 11 Violin Plots
- 12 Bean Plots
- 13 Bubble Charts
- 14 3D Surface Plot
- 15 Chernoff Faces—Graphical Presentation of Multivariate Data
- 16 Maps

- Chapter 4: Matrix Algebra Topics in Statistics and Economics Using R
- Abstract
- 1 Introduction
- 2 Basic Matrix Manipulations in R
- 3 Descriptive Statistics
- 4 Matrix Transformations, Invariance, and Equivariance
- 5 Payoff Matrices in Decision Analysis
- 6 Matrix Algebra in Regression Models
- 7 Correlation Matrices and Generalizations
- 8 Matrices for Population Dynamics
- 9 Multivariate Components Analysis
- 10 Sparse Matrices

- Chapter 5: Sample Size Calculations with R: Level 1
- Abstract
- 1 Introduction
- 2 General Ideas on Sample Size Calculations
- 3 Single-Sample Problems
- 4 Two-Sample Problems: Quantitative Responses
- 5 Multisample Problem—Quantitative Responses—Analysis of Variance

- Chapter 6: Sample Size Calculations with R: Level 2
- Abstract
- 1 Single Proportions
- 2 Two-Sample Proportions
- 3 Effect Sizes
- 4 Multisample Proportions
- 5 McNemar Test
- 6 Correlations
- 7 Hazard Ratio in Survival Analysis
- 8 Multiple Regression

- Chapter 7: Binomial Regression in R
- Abstract
- 1 Binomial Regression in the Generalized Linear Model
- 2 Standard Logistic Regression
- 3 Assumptions Involved in the Standard Logistic Regression Model
- 4 Residuals
- 5 Overdispersion
- 6 Hypothesis Testing and Inference
- 7 Model Performance
- 8 Modeling Repeated (Longitudinal) Binary Measures
- 9 Model Selection
- 10 Machine Learning Methods
- 11 Concluding Remarks

- Chapter 8: Computing Tolerance Intervals and Regions Using R
- Abstract
- 1 Introduction
- 2 Tolerance Intervals for Continuous Distributions
- 3 Tolerance Intervals for Discrete Distributions
- 4 Nonparametric Tolerance Intervals
- 5 Regression Tolerance Intervals
- 6 Multivariate Tolerance Regions
- 7 Final Remarks

- Chapter 9: Modeling the Probability of Second Cancer in Controlled Clinical Trials
- Abstract
- 1 Introduction
- 2 Difficulties in Second Cancer Research
- 3 Current Knowledge of Second Malignancy
- 4 Clinical Trial Database
- 5 Integrated Analysis
- 6 Assessing Model Adequacy
- 7 Summary

- Chapter 10: Bayesian Networks
- Abstract
- 1 Introduction
- 2 Joint and Conditional Distributions
- 3 Generalities and Issues
- 4 Graph Theory
- 5 A Case Study
- 6 Network Model Fitting
- 7 Learning Algorithm

- Subject Index

- No. of pages: 412
- Language: English
- Edition: 1
- Volume: 32
- Published: November 25, 2014
- Imprint: Elsevier
- Hardback ISBN: 9780444634313
- eBook ISBN: 9780444634412

MR

### Marepalli B. Rao

CR

### C.R. Rao

He retired from ISI in 1980 at the mandatory age of 60 after working for 40 years during which period he developed ISI as an international center for statistical education and research. He also took an active part in establishing state statistical bureaus to collect local statistics and transmitting them to Central Statistical Organization in New Delhi. Rao played a pivitol role in launching undergraduate and postgraduate courses at ISI. He is the author of 475 research publications and several breakthrough papers contributing to statistical theory and methodology for applications to problems in all areas of human endeavor. There are a number of classical statistical terms named after him, the most popular of which are Cramer-Rao inequality, Rao-Blackwellization, Rao’s Orthogonal arrays used in quality control, Rao’s score test, Rao’s Quadratic Entropy used in ecological work, Rao’s metric and distance which are incorporated in most statistical books.

He is the author of 10 books, of which two important books are, Linear Statistical Inference which is translated into German, Russian, Czec, Polish and Japanese languages,and Statistics and Truth which is translated into, French, German, Japanese, Mainland Chinese, Taiwan Chinese, Turkish and Korean languages.

He directed the research work of 50 students for the Ph.D. degrees who in turn produced 500 Ph.D.’s. Rao received 38 hon. Doctorate degree from universities in 19 countries spanning 6 continents. He received the highest awards in statistics in USA,UK and India: National Medal of Science awarded by the president of USA, Indian National Medal of Science awarded by the Prime Minister of India and the Guy Medal in Gold awarded by the Royal Statistical Society, UK. Rao was a recipient of the first batch of Bhatnagar awards in 1959 for mathematical sciences and and numerous medals in India and abroad from Science Academies. He is a Fellow of Royal Society (FRS),UK, and member of National Academy of Sciences, USA, Lithuania and Europe. In his honor a research Institute named as CRRAO ADVANCED INSTITUTE OF MATHEMATICS, STATISTICS AND COMPUTER SCIENCE was established in the campus of Hyderabad University.