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该书链接：http://oreilly.com/catalog/9780596801717
http://www.amazon.com/R-Nutshell ... rence/dp/059680170X
- R Basics
- Chapter 1 Getting and Installing R
- R Versions
- Getting and Installing Interactive R Binaries
- Chapter 2 The R User Interface
- The R Graphical User Interface
- The R Console
- Batch Mode
- Using R Inside Microsoft Excel
- Other Ways to Run R
- Chapter 3 A Short R Tutorial
- Basic Operations in R
- Functions
- Variables
- Introduction to Data Structures
- Objects and Classes
- Models and Formulas
- Charts and Graphics
- Getting Help
- Chapter 4 R Packages
- An Overview of Packages
- Listing Packages in Local Libraries
- Loading Packages
- Exploring Package Repositories
- Custom Packages
- Chapter 1 Getting and Installing R
- The R Language
- Chapter 5 An Overview of the R Language
- Expressions
- Objects
- Symbols
- Functions
- Objects Are Copied in Assignment Statements
- Everything in R Is an Object
- Special Values
- Coercion
- The R Interpreter
- Seeing How R Works
- Chapter 6 R Syntax
- Constants
- Operators
- Expressions
- Control Structures
- Accessing Data Structures
- R Code Style Standards
- Chapter 7 R Objects
- Primitive Object Types
- Vectors
- Lists
- Other Objects
- Attributes
- Chapter 8 Symbols and Environments
- Symbols
- Working with Environments
- The Global Environment
- Environments and Functions
- Exceptions
- Chapter 9 Functions
- The Function Keyword
- Arguments
- Return Values
- Functions As Arguments
- Argument Order and Named Arguments
- Side Effects
- Chapter 10 Object-Oriented Programming
- Overview of Object-Oriented Programming in R
- Object-Oriented Programming in R: S4 Classes
- Old-School OOP in R: S3
- Chapter 11 High-Performance R
- Use Built-in Math Functions
- Use Environments for Lookup Tables
- Use a Database to Query Large Data Sets
- Preallocate Memory
- Monitor How Much Memory You Are Using
- Functions for Big Data Sets
- Parallel Computation with R
- High-Performance R Binaries
- Chapter 5 An Overview of the R Language
- Working with Data
- Chapter 12 Saving, Loading, and Editing Data
- Entering Data Within R
- Saving and Loading R Objects
- Importing Data from External Files
- Exporting Data
- Importing Data from Databases
- Chapter 13 Preparing Data
- Combining Data Sets
- Transformations
- Binning Data
- Subsets
- Summarizing Functions
- Data Cleaning
- Finding and Removing Duplicates
- Sorting
- Chapter 14 Graphics
- An Overview of R Graphics
- Graphics Devices
- Customizing Charts
- Chapter 15 Lattice Graphics
- History
- An Overview of the Lattice Package
- High-Level Lattice Plotting Functions
- Customizing Lattice Graphics
- Low-Level Functions
- Chapter 12 Saving, Loading, and Editing Data
- Statistics with R
- Chapter 16 Analyzing Data
- Summary Statistics
- Correlation and Covariance
- Principal Components Analysis
- Factor Analysis
- Bootstrap Resampling
- Chapter 17 Probability Distributions
- Normal Distribution
- Common Distribution-Type Arguments
- Distribution Function Families
- Chapter 18 Statistical Tests
- Continuous Data
- Discrete Data
- Chapter 19 Power Tests
- Experimental Design Example
- t-Test Design
- Proportion Test Design
- ANOVA Test Design
- Chapter 20 Regression Models
- Example: A Simple Linear Model
- Details About the lm Function
- Subset Selection and Shrinkage Methods
- Nonlinear Models
- Survival Models
- Smoothing
- Machine Learning Algorithms for Regression
- Chapter 21 Classification Models
- Linear Classification Models
- Machine Learning Algorithms for Classification
- Chapter 22 Machine Learning
- Market Basket Analysis
- Clustering
- Chapter 23 Time Series Analysis
- Autocorrelation Functions
- Time Series Models
- Chapter 24 Bioconductor
- An Example
- Key Bioconductor Packages
- Data Structures
- Where to Go Next
- Chapter 16 Analyzing Data
- Appendix R Reference
- base
- boot
- class
- cluster
- codetools
- foreign
- grDevices
- graphics
- grid
- KernSmooth
- lattice
- MASS
- methods
- mgcv
- nlme
- nnet
- rpart
- spatial
- splines
- stats
- stats4
- survival
- tcltk
- tools
- utils
- Bibliography
- Colophon
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