Computational statistics with R / [edited by] Marepalli B. Rao and C.R. Rao.
Series: Handbook of statistics ; v 32.Publication details: Amsterdam : Elsevier, ©2014.Description: xvii, 394 p. ; illustrationsISBN:- 9780444634313
- 000SA.055 23 R215
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000SA.055 M652 OpenStat reference manual / | 000SA.055 N251 Nonlinear parameter optimization using R tools / | 000SA.055 N787 Data science in R : | 000SA.055 R215 Computational statistics with R / | 000SA.055 R236 Statistical and machine-learning data mining : techniques for better predictive modeling and analysis of big data / | 000SA.055 Sa158 Three stochastic models on discrete structures / | 000SA.055 Sch392 Understanding statistics using R / |
Includes bibliographical references and index.
1. Introduction to R --
2. R graphics --
3. Graphics miscellanea --
4. Matrix algebra topics in statistics and economics using R --
5. Sample size calculations with R: level 1 --
6. Sample size calculations with R: level 2 --
7. Bionomial regression in R --
8. Computing tolerance intervals and regions using R --
9. Modeling the probability of second cancer in controlled clinical trials --
10. Bayesian networks.
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.
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