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R for Everyone: Advanced Analytics and Graphics
Using the free, open source R language, scientists, financial analysts, public policy professionals, and programmers can build powerful statistical models capable of answering many of their most challenging questions. But, for non-statisticians, R can be difficult to learn-and most books on the subj...
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| Format: | Printed Book |
| Published: |
Noida
Pearson Education
2014
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| Series: | Addison-Wesley data and analytics series.
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| Subjects: |
Table of Contents:
- 1. Getting R
- 1.1. Downloading R
- 1.2.R Version
- 1.3.32-bit versus 64-bit
- 1.4. Installing
- 1.5. Revolution R Community Edition
- 1.6. Conclusion
- 2. The R Environment
- 2.1.Command Line Interface
- 2.2. RStudio
- 2.3. Revolution Analytics RPE
- 2.4. Conclusion
- 3.R Packages
- 3.1. Installing Packages
- 3.2. Loading Packages
- 3.3. Building a Package
- 3.4. Conclusion
- 4. Basics of R
- 4.1. Basic Math
- 4.2. Variables
- 4.3. Data Types
- 4.4. Vectors
- 4.5. Calling Functions
- 4.6. Function Documentation
- 4.7. Missing Data
- 4.8. Conclusion
- 5. Advanced Data Structures
- 5.1.data.frames
- 5.2. Lists
- 5.3. Matrices
- 5.4. Arrays
- 5.5. Conclusion
- 6. Reading Data into R
- 6.1. Reading CSVs
- 6.2. Excel Data
- 6.3. Reading from Databases
- 6.4. Data from Other Statistical Tools
- 6.5.R Binary Files
- 6.6. Data Included with R
- 6.7. Extract Data from Web Sites
- 6.8. Conclusion
- 7. Statistical Graphics
- 7.1. Base Graphics
- 7.2.ggplot2
- 7.3. Conclusion
- 8. Writing R Functions
- 8.1. Hello, World!
- 8.2. Function Arguments
- 8.3. Return Values
- 8.4.do. call
- 8.5. Conclusion
- 9. Control Statements
- 9.1. If and else
- 9.2.switch
- 9.3.ifelse
- 9.4.Compound Tests
- 9.5. Conclusion
- 10. Loops, the Un-R Way to Iterate
- 10.1. For Loops
- 10.2. While Loops
- 10.3. Controlling Loops
- 10.4. Conclusion
- 11. Group Manipulation
- 11.1. Apply Family
- 11.2.aggregate
- 11.3.plyr
- 11.4.data.table
- 11.5. Conclusion
- 12. Data Reshaping
- 12.1.cbind and rbind
- 12.2. Joins
- 12.3.reshape2
- 12.4. Conclusion
- 13. Manipulating Strings
- 13.1.paste
- 13.2.sprintf
- 13.3. Extracting Text
- 13.4. Regular Expressions
- 13.5. Conclusion
- 14. Probability Distributions
- 14.1. Normal Distribution
- 14.2. Binomial Distribution
- 14.3. Poisson Distribution
- 14.4. Other Distributions
- 14.5. Conclusion
- 15. Basic Statistics
- 15.1. Summary Statistics
- 15.2. Correlation and Covariance
- 15.3.T-Tests
- 15.4. ANOVA
- 15.5. Conclusion
- 16. Linear Models
- 16.1. Simple Linear Regression
- 16.2. Multiple Regression
- 16.3. Conclusion
- 17. Generalized Linear Models
- 17.1. Logistic Regression
- 17.2. Poisson Regression
- 17.3. Other Generalized Linear Models
- 17.4. Survival Analysis
- 17.5. Conclusion
- 18. Model Diagnostics
- 18.1. Residuals
- 18.2.Comparing Models
- 18.3. Cross-Validation
- 18.4. Bootstrap
- 18.5. Stepwise Variable Selection
- 18.6. Conclusion
- 19. Regularization and Shrinkage
- 19.1. Elastic Net
- 19.2. Bayesian Shrinkage
- 19.3. Conclusion
- 20. Nonlinear Models
- 20.1. Nonlinear Least Squares
- 20.2. Splines
- 20.3. Generalized Additive Models
- 20.4. Decision Trees
- 20.5. Random Forests
- 20.6. Conclusion
- 21. Time Series and Autocorrelation
- 21.1. Autoregressive Moving Average
- 21.2. VAR
- 21.3. GARCH
- 21.4. Conclusion
- 22. Clustering
- 22.1.K-means
- 22.2. PAM
- 22.3. Hierarchical Clustering
- 22.4. Conclusion
- 23. Reproducibility, Reports and Slide Shows with knitr
- 23.1. Installing LATEX Program
- 23.2. LATEX Primer
- 23.3. Using knitr with LATEX
- 23.4. Markdown Tips
- 23.5. Using knitr and Markdown
- 23.6.pandoc
- 23.7. Conclusion
- 24. Building R Packages
- 24.1. Folder Structure
- 24.2. Package Files
- 24.3. Package Documentation
- 24.4. Checking, Building and Installing
- 24.5. Submitting to CRAN
- 24.6.C++ Code
- 24.7. Conclusion
- A. Real-Life Resources
- A.1. Meetups
- A.2. Stackoverflow
- A.3. Twitter
- A.4. Conferences
- A.5. Web Sites
- A.6. Documents
- A.7. Books
- A.8. Conclusion
- B. Glossary.