今天在网上闲逛的时候，看到一本书R in nutshell, 好像不错，不知哪位有电子版？
R in a Nutshell-A Desktop Quick ReferenceBy Joseph Adler Publisher: O'Reilly Media Released: December 2009 Pages: 640

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
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
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
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

Appendix R Reference
basebootclassclustercodetoolsforeigngrDevicesgraphicsgridKernSmoothlatticeMASSmethodsmgcvnlmennetrpartspatialsplinesstatsstats4survivaltcltktools
• utils
Bibliography
• Colophon