R框架、包和软件集合：Awesome R

Love The Way You Lie 2022-08-18 13:27 128阅读 0赞

阅读目录

*  [Integrated Development Environment][]
 *  [Data Manipulation][]
 *  [Graphic Displays][]
 *  [Reproducible Research][]
 *  [Web Technologies and Services][]
 *  [Parallel Computing][]
 *  [High Performance][]
 *  [Language API][]
 *  [Database Management][]
 *  [Machine Learning][]
 *  [Natural Language Processing][]
 *  [Bayesian][]
 *  [Finance][]
 *  [Genetics][]
 *  [R Development][]
 *  [Other Interpreter][]
 *  [Websites][]
 *  [Books][]
 *  [Reference Card][]

R框架、包和软件集合：Awesome R。

*  [Awesome R][]
    
     *  [Integrated Development Environment][Integrated Development Environment 1]
     *  [Data Manipulation][Data Manipulation 1]
     *  [Graphic Displays][Graphic Displays 1]
     *  [Reproducible Research][Reproducible Research 1]
     *  [Web Technologies and Services][Web Technologies and Services 1]
     *  [Parallel Computing][Parallel Computing 1]
     *  [High Performance][High Performance 1]
     *  [Language API][Language API 1]
     *  [Database Management][Database Management 1]
     *  [Machine Learning][Machine Learning 1]
     *  [Natural Language Processing][Natural Language Processing 1]
     *  [Bayesian][Bayesian 1]
     *  [Finance][Finance 1]
     *  [Genetics][Genetics 1]
     *  [R Development][R Development 1]
     *  [Other Interpreter][Other Interpreter 1]
 *  [Resources][]
    
     *  [Websites][Websites 1]
     *  [Books][Books 1]
     *  [Reference Card][Reference Card 1]
 *  [Other Awesome Lists][]
 *  [Contributing][]

## Integrated Development Environment ##

Integrated Development Environment

*  [RStudio][] - A powerful and productive user interface for R. Works great on Windows, Mac, and Linux.
 *  [JGR][] - JGR (speak 'Jaguar') is a Java Gui for R.
 *  [Emacs + ESS][Emacs _ ESS] - Emacs Speaks Statistics is an add-on package for emacs text editors.
 *  [StatET][] - An Eclipse based IDE (integrated development environment) for R.
 *  [Revolution R Enterprise][] - Revolution R would be offered free to academic users and commercial software would focus on big data, large scale multiprocessor functionality.
 *  [R Commander][] - A package that provides a basic graphical user interface.
 *  [IPython][] - An interactive Python interpreter,and it supports execution of R code while capturing both output and figures.
 *  [Deducer][] - A Menu driven data analysis GUI with a spreadsheet like data editor.

[回到顶部][Link 1]

## Data Manipulation ##

Packages for cooking data.

*  [dplyr][] - Blazing fast data frames manipulation and database query.
 *  [data.table][] - Fast data manipulation in a short and flexible syntax.
 *  [reshape2][] - Flexible rearrange, reshape and aggregate data.
 *  [tidyr][] - Easily tidy data with spread and gather functions.

[回到顶部][Link 1]

## Graphic Displays ##

Packages for showing data.

*  [ggplot2][] - An implementation of the Grammar of Graphics.
 *  [ggvis][] - Interactive grammar of graphics for R.
 *  [rCharts][] - Interactive JS Charts from R.
 *  [lattice][] - A powerful and elegant high-level data visualization system.
 *  [rgl][] - 3D visualization device system for R.
 *  [Cairo][] - R graphics device using cairo graphics library for creating high-quality display output.
 *  [extrafont][] - Tools for using fonts in R graphics.
 *  [showtext][] - Enable R graphics device to show text using system fonts.

[回到顶部][Link 1]

## Reproducible Research ##

Packages for literate programming.

*  [knitr][] - Easy dynamic report generation in R.
 *  [xtable][] - Export tables to LaTeX or HTML.
 *  [rapport][] - An R templating system.
 *  [rmarkdown][] - Dynamic documents for R.

[回到顶部][Link 1]

## Web Technologies and Services ##

Packages to surf the web.

*  [shiny][] - Easy interactive web applications with R.
 *  [RCurl][] - General network (HTTP/FTP/...) client interface for R.
 *  [httpuv][] - HTTP and WebSocket server library.
 *  [XML][] - Tools for parsing and generating XML within R.

[回到顶部][Link 1]

## Parallel Computing ##

Packages for parallel computing.

*  [parallel][] - R started with release 2.14.0 which includes a new package parallel incorporating (slightly revised) copies of packages [multicore][] and [snow][].
 *  [Rmpi][] - Rmpi provides an interface (wrapper) to MPI APIs. It also provides interactive R slave environment.
 *  [foreach][] - Executing the loop in parallel

[回到顶部][Link 1]

## High Performance ##

Packages for making R faster.

*  [Rcpp][] - Rcpp provides a powerful API on top of R, make function in R extremely faster.
 *  [Rcpp11][] - Rcpp11 is a complete redesign of Rcpp, targetting C++11.
 *  [compiler][] - speeding up your R code using the JIT

[回到顶部][Link 1]

## Language API ##

Packages for other languages.

*  [rJava][] - Low-level R to Java interface.
 *  [jvmr][] - Integration of R, Java, and Scala.
 *  [rJython][] - R interface to Python via Jython.
 *  [rPython][] - Package allowing R to call Python.
 *  [runr][] - Run Julia and Bash from R.
 *  [RJulia][] - R package Call Julia.
 *  [RinRuby][] - a Ruby library that integrates the R interpreter in Ruby.
 *  [R.matlab][] - Read and write of MAT files together with R-to-MATLAB connectivity.
 *  [RcppOctave][] - Seamless Interface to Octave and Matlab.
 *  [RSPerl][] - A bidirectional interface for calling R from Perl and Perl from R.

[回到顶部][Link 1]

## Database Management ##

Packages for managing data.

*  [RODBC][] - ODBC database access for R.
 *  [DBI][] - Defines a common interface between the R and database management systems.
 *  [RMySQL][] - R interface to the MySQL database.
 *  [ROracle][] - OCI based Oracle database interface for R.
 *  [RPostgreSQL][] - R interface to the PostgreSQL database system.
 *  [RSQLite][] - SQLite interface for R
 *  [RJDBC][] - Provides access to databases through the JDBC interface.
 *  [rmongodb][] - R driver for MongoDB.
 *  [rredis][] - Redis client for R.
 *  [RCassandra][] - Direct interface (not Java) to the most basic functionality of Apache Cassanda.
 *  [RHive][] - R extension facilitating distributed computing via Apache Hive.

[回到顶部][Link 1]

## Machine Learning ##

Packages for making R cleverer.

*  [h2o][] - Deeplearning, Random forests, GBM, KMeans, PCA, GLM
 *  [Clever Algorithms For Machine Learning][]
 *  [Machine Learning For Hackers][]
 *  [rpart][] - Recursive Partitioning and Regression Trees
 *  [randomForest][] - Breiman and Cutler's random forests for classification and regression
 *  [lasso2][] - L1 constrained estimation aka ‘lasso’
 *  [gbm][] - Generalized Boosted Regression Models
 *  [e1071][] - Misc Functions of the Department of Statistics (e1071), TU Wien
 *  [tgp][] - Bayesian treed Gaussian process models
 *  [rgp][] - R genetic programming framework
 *  [arules][] - Mining Association Rules and Frequent Itemsets
 *  [frbs][] - Fuzzy Rule-based Systems for Classification and Regression Tasks
 *  [rattle][] - Graphical user interface for data mining in R
 *  [ahaz][] - Regularization for semiparametric additive hazards regression
 *  [arules][] - Mining Association Rules and Frequent Itemsets
 *  [bigrf][] - Big Random Forests: Classification and Regression Forests for Large Data Sets
 *  [bigRR][] - Generalized Ridge Regression (with special advantage for p >> n cases)
 *  [bmrm][] - Bundle Methods for Regularized Risk Minimization Package
 *  [Boruta][] - A wrapper algorithm for all-relevant feature selection
 *  [bst][] - Gradient Boosting
 *  [C50][] - C5.0 Decision Trees and Rule-Based Models
 *  [caret][] - Classification and Regression Training
 *  [CORElearn][] - Classification, regression, feature evaluation and ordinal evaluation
 *  [CoxBoost][] - Cox models by likelihood based boosting for a single survival endpoint or competing risks
 *  [Cubist][] - Rule- and Instance-Based Regression Modeling
 *  [earth][] - Multivariate Adaptive Regression Spline Models
 *  [elasticnet][] - Elastic-Net for Sparse Estimation and Sparse PCA
 *  [ElemStatLearn][] - Data sets, functions and examples from the book: "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
 *  [evtree][] - Evolutionary Learning of Globally Optimal Trees
 *  [frbs][] - Fuzzy Rule-based Systems for Classification and Regression Tasks
 *  [GAMBoost][] - Generalized linear and additive models by likelihood based boosting
 *  [gamboostLSS][] - Boosting Methods for GAMLSS
 *  [gbm][] - Generalized Boosted Regression Models
 *  [glmnet][] - Lasso and elastic-net regularized generalized linear models
 *  [glmpath][] - L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model
 *  [GMMBoost][] - Likelihood-based Boosting for Generalized mixed models
 *  [grplasso][] - Fitting user specified models with Group Lasso penalty
 *  [grpreg][] - Regularization paths for regression models with grouped covariates
 *  [hda][] - Heteroscedastic Discriminant Analysis
 *  [ipred][] - Improved Predictors
 *  [kernlab][] - kernlab: Kernel-based Machine Learning Lab
 *  [klaR][] - Classification and visualization
 *  [lars][] - Least Angle Regression, Lasso and Forward Stagewise
 *  [lasso2][] - L1 constrained estimation aka ‘lasso’
 *  [LiblineaR][] - Linear Predictive Models Based On The Liblinear C/C++ Library
 *  [LogicReg][] - Logic Regression
 *  [maptree][] - Mapping, pruning, and graphing tree models
 *  [mboost][] - Model-Based Boosting
 *  [mvpart][] - Multivariate partitioning
 *  [ncvreg][] - Regularization paths for SCAD- and MCP-penalized regression models
 *  [nnet][] - eed-forward Neural Networks and Multinomial Log-Linear Models
 *  [oblique.tree][] - Oblique Trees for Classification Data
 *  [pamr][] - Pam: prediction analysis for microarrays
 *  [party][] - A Laboratory for Recursive Partytioning
 *  [partykit][] - A Toolkit for Recursive Partytioning
 *  [penalized][] - L1 (lasso and fused lasso) and L2 (ridge) penalized estimation in GLMs and in the Cox model
 *  [penalizedLDA][] - Penalized classification using Fisher's linear discriminant
 *  [penalizedSVM][] - Feature Selection SVM using penalty functions
 *  [quantregForest][] - quantregForest: Quantile Regression Forests
 *  [randomForest][] - randomForest: Breiman and Cutler's random forests for classification and regression
 *  [randomForestSRC][] - randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC)
 *  [rda][] - Shrunken Centroids Regularized Discriminant Analysis
 *  [rdetools][] - Relevant Dimension Estimation (RDE) in Feature Spaces
 *  [REEMtree][] - Regression Trees with Random Effects for Longitudinal (Panel) Data
 *  [relaxo][] - Relaxed Lasso
 *  [rgenoud][] - R version of GENetic Optimization Using Derivatives
 *  [rgp][] - R genetic programming framework
 *  [Rmalschains][] - Continuous Optimization using Memetic Algorithms with Local Search Chains (MA-LS-Chains) in R
 *  [rminer][] - Simpler use of data mining methods (e.g. NN and SVM) in classification and regression
 *  [ROCR][] - Visualizing the performance of scoring classifiers
 *  [RoughSets][] - Data Analysis Using Rough Set and Fuzzy Rough Set Theories
 *  [rpart][] - Recursive Partitioning and Regression Trees
 *  [RPMM][] - Recursively Partitioned Mixture Model
 *  [RSNNS][] - Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS)
 *  [RWeka][] - R/Weka interface
 *  [RXshrink][] - RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least Angle Regression
 *  [sda][] - Shrinkage Discriminant Analysis and CAT Score Variable Selection
 *  [SDDA][] - Stepwise Diagonal Discriminant Analysis
 *  [svmpath][] - svmpath: the SVM Path algorithm
 *  [tgp][] - Bayesian treed Gaussian process models
 *  [tree][] - Classification and regression trees
 *  [varSelRF][] - Variable selection using random forests
 *  [caret][caret 1] - Unified interface to ~150 ML algorithms in R.
 *  [SuperLearner][] and [subsemble][] - Multi-algorithm ensemble learning packages.
 *  [Introduction to Statistical Learning][]

[回到顶部][Link 1]

## Natural Language Processing ##

Packages for Natural Language Processing.

*  [tm][] - A comprehensive text mining framework for R.
 *  [openNLP][] - Apache OpenNLP Tools Interface.
 *  [koRpus][] - An R Package for Text Analysis.
 *  [zipfR][] - Statistical models for word frequency distributions.
 *  [tmcn][] - A Text mining toolkit for international characters especially for Chinese.
 *  [rmmseg4j][] - R interface to the Java Chinese word segmentation system of mmseg4j.
 *  [Rwordseg][] - Chinese word segmentation.

[回到顶部][Link 1]

## Bayesian ##

Packages for Bayesian Inference.

*  [coda][] - Output analysis and diagnostics for MCMC.
 *  [mcmc][] - Markov Chain Monte Carlo.
 *  [MCMCpack][] - Markov chain Monte Carlo (MCMC) Package.
 *  [R2WinBUGS][] - Running WinBUGS and OpenBUGS from R / S-PLUS.
 *  [BRugs][] - R interface to the OpenBUGS MCMC software.

[回到顶部][Link 1]

## Finance ##

Packages for dealing with money.

*  [quantmod][] - Quantitative Financial Modelling & Trading Framework for R.
 *  [TTR][] - Functions and data to construct technical trading rules with R.
 *  [PerformanceAnalytics][] - Econometric tools for performance and risk analysis.
 *  [zoo][] - S3 Infrastructure for Regular and Irregular Time Series.
 *  [xts][] - eXtensible Time Series.
 *  [tseries][] - Time series analysis and computational finance.
 *  [fAssets][] - Analysing and Modelling Financial Assets.

[回到顶部][Link 1]

## Genetics ##

Packages for Statistical Genetics.

*  [Bioconductor][] - Tools for the analysis and comprehension of high-throughput genomic data.
 *  [genetics][] - Classes and methods for handling genetic data.
 *  [gap][] - An integrated package for genetic data analysis of both population and family data.
 *  [ape][] - Analyses of Phylogenetics and Evolution.

[回到顶部][Link 1]

## R Development ##

Packages for packages.

*  [devtools][] - Tools to make an R developer's life easier.
 *  [testthat][] - An R package to make testing fun.
 *  [R6][] - simpler, faster, lighter-weight alternative to R's built-in classes.
 *  [pryr][] - Make it easier to understand what's going on in R.
 *  [roxygen][] - Describe your functions in comments next to their definitions.
 *  [lineprof][] - Visualise line profiling results in R.
 *  [packrat][] - Make your R projects more isolated, portable, and reproducible.
 *  [installr][] - Functions for installing softwares from within R.

[回到顶部][Link 1]

## Other Interpreter ##

Alternative R engines.

*  [renjin][] - a JVM-based interpreter for R.
 *  [pqR][] - a "pretty quick" implementation of R
 *  [fastR][] - FastR is an implementation of the R Language in Java atop Truffle and Graal.
 *  [riposte][] - a fast interpreter and JIT for R.
 *  [TERR][] - TIBCO Enterprise Runtime for R.
 *  [RRE][] - Revolution R Enterprise.
 *  [CXXR][] - Refactorising R into C++.

# Resources #

Where to discover new R-esources.

[回到顶部][Link 1]

## Websites ##

*  [R-project][] - The R Project for Statistical Computing.
 *  [R Bloggers][] - There are people scattered across the Web who blog about R. This is simply an aggregator of many of those feeds.
 *  [DataCamp][] - Learn R data analytics online.
 *  [Quick-R][] - An excellent quick reference.
 *  [Advanced R][] - An in-progress book site for Advanced R.
 *  [CRAN Task Views][] - Task Views for CRAN packages.

[回到顶部][Link 1]

## Books ##

*  [The Art of R Programming][] - It's a good resource for systematically learning fundamentals such as types of objects, control statements, variable scope, classes and debugging in R.
 *  [R in Action][] - This book aims at all levels of users, with sections for beginning, intermediate and advanced R ranging from "Exploring R data structures" to running regressions and conducting factor analyses.
 *  [Use R!][Use R] - This series of inexpensive and focused books from Springer publish shorter books aimed at practitioners. Books can discuss the use of R in a particular subject area, such as bayesian networks, ggplot2 and Rcpp.

[回到顶部][Link 1]

## Reference Card ##

*  [R Reference Card 2.0][R_Reference_Card_2.0] - Material from R for Beginners by permission of Emmanuel Paradis (Version 2 by Matt Baggott).
 *  [Data Mining Refcard][] - R Reference Card for Data Mining.
 *  [Regression Analysis Refcard][] - R Reference Card for Regression Analysis.
 *  [Reference Card for ESS][] - Reference Card for ESS.
 *  [R Markdown Cheat sheet][] - Quick reference guide for writing reports with R Markdown.
 *  [Shiny Cheat sheet][] - Quick reference guide for building Shiny apps.

# Other Awesome Lists #

*  [awesome-awesomeness][]
 *  [lists][]

项目主页：[http://www.open-open.com/lib/view/home/1413446023903][http_www.open-open.com_lib_view_home_1413446023903]

[Integrated Development Environment]: http://www.open-open.com/lib/view/open1413446023903.html#_label0
[Data Manipulation]: http://www.open-open.com/lib/view/open1413446023903.html#_label1
[Graphic Displays]: http://www.open-open.com/lib/view/open1413446023903.html#_label2
[Reproducible Research]: http://www.open-open.com/lib/view/open1413446023903.html#_label3
[Web Technologies and Services]: http://www.open-open.com/lib/view/open1413446023903.html#_label4
[Parallel Computing]: http://www.open-open.com/lib/view/open1413446023903.html#_label5
[High Performance]: http://www.open-open.com/lib/view/open1413446023903.html#_label6
[Language API]: http://www.open-open.com/lib/view/open1413446023903.html#_label7
[Database Management]: http://www.open-open.com/lib/view/open1413446023903.html#_label8
[Machine Learning]: http://www.open-open.com/lib/view/open1413446023903.html#_label9
[Natural Language Processing]: http://www.open-open.com/lib/view/open1413446023903.html#_label10
[Bayesian]: http://www.open-open.com/lib/view/open1413446023903.html#_label11
[Finance]: http://www.open-open.com/lib/view/open1413446023903.html#_label12
[Genetics]: http://www.open-open.com/lib/view/open1413446023903.html#_label13
[R Development]: http://www.open-open.com/lib/view/open1413446023903.html#_label14
[Other Interpreter]: http://www.open-open.com/lib/view/open1413446023903.html#_label15
[Websites]: http://www.open-open.com/lib/view/open1413446023903.html#_label16
[Books]: http://www.open-open.com/lib/view/open1413446023903.html#_label17
[Reference Card]: http://www.open-open.com/lib/view/open1413446023903.html#_label18
[Awesome R]: https://github.com/qinwf/awesome-R#awesome-r
[Integrated Development Environment 1]: https://github.com/qinwf/awesome-R#integrated-development-environment
[Data Manipulation 1]: https://github.com/qinwf/awesome-R#data-manipulation
[Graphic Displays 1]: https://github.com/qinwf/awesome-R#graphic-displays
[Reproducible Research 1]: https://github.com/qinwf/awesome-R#reproducible-research
[Web Technologies and Services 1]: https://github.com/qinwf/awesome-R#web-technologies-and-services
[Parallel Computing 1]: https://github.com/qinwf/awesome-R#parallel-computing
[High Performance 1]: https://github.com/qinwf/awesome-R#high-performance
[Language API 1]: https://github.com/qinwf/awesome-R#language-api
[Database Management 1]: https://github.com/qinwf/awesome-R#database-management
[Machine Learning 1]: https://github.com/qinwf/awesome-R#machine-learning
[Natural Language Processing 1]: https://github.com/qinwf/awesome-R#natural-language-processing
[Bayesian 1]: https://github.com/qinwf/awesome-R#bayesian
[Finance 1]: https://github.com/qinwf/awesome-R#finance
[Genetics 1]: https://github.com/qinwf/awesome-R#genetics
[R Development 1]: https://github.com/qinwf/awesome-R#r-development
[Other Interpreter 1]: https://github.com/qinwf/awesome-R#other-interpreter
[Resources]: https://github.com/qinwf/awesome-R#resources
[Websites 1]: https://github.com/qinwf/awesome-R#websites
[Books 1]: https://github.com/qinwf/awesome-R#books
[Reference Card 1]: https://github.com/qinwf/awesome-R#reference-card
[Other Awesome Lists]: https://github.com/qinwf/awesome-R#other-awesome-lists
[Contributing]: https://github.com/qinwf/awesome-R#contributing
[RStudio]: http://www.rstudio.org/
[JGR]: http://rforge.net/JGR/
[Emacs _ ESS]: http://ess.r-project.org/
[StatET]: http://www.walware.de/goto/statet
[Revolution R Enterprise]: http://www.revolutionanalytics.com/get-revolution-r-enterprise
[R Commander]: http://socserv.mcmaster.ca/jfox/Misc/Rcmdr/
[IPython]: http://ipython.org/ipython-doc/rel-0.13/config/extensions/rmagic.html#extensions-rmagic
[Deducer]: http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual?from=Main.HomePage
[Link 1]: http://www.open-open.com/lib/view/open1413446023903.html#_labelTop
[dplyr]: https://github.com/hadley/dplyr
[data.table]: https://github.com/Rdatatable/data.table
[reshape2]: https://github.com/hadley/reshape
[tidyr]: https://github.com/hadley/tidyr
[ggplot2]: https://github.com/hadley/ggplot2
[ggvis]: https://github.com/rstudio/ggvis
[rCharts]: https://github.com/ramnathv/rCharts
[lattice]: http://lattice.r-forge.r-project.org/
[rgl]: http://cran.r-project.org/web/packages/rgl/index.html
[Cairo]: http://cran.r-project.org/web/packages/Cairo/index.html
[extrafont]: https://github.com/wch/extrafont
[showtext]: https://github.com/yixuan/showtext
[knitr]: http://yihui.name/knitr/
[xtable]: http://cran.r-project.org/web/packages/xtable/index.html
[rapport]: http://rapport-package.info/#intro
[rmarkdown]: http://rmarkdown.rstudio.com/
[shiny]: https://github.com/rstudio/shiny
[RCurl]: http://cran.r-project.org/web/packages/RCurl/index.html
[httpuv]: https://github.com/rstudio/httpuv
[XML]: http://cran.r-project.org/web/packages/XML/index.html
[parallel]: http://cran.r-project.org/web/views/HighPerformanceComputing.html
[multicore]: http://cran.r-project.org/web/packages/multicore/index.html
[snow]: http://cran.r-project.org/web/packages/snow/index.html
[Rmpi]: http://cran.r-project.org/web/packages/Rmpi/index.html
[foreach]: http://cran.r-project.org/web/packages/foreach/index.html
[Rcpp]: http://rcpp.org/
[Rcpp11]: https://github.com/Rcpp11
[compiler]: http://stat.ethz.ch/R-manual/R-devel/library/compiler/html/compile.html
[rJava]: http://cran.r-project.org/web/packages/rJava/
[jvmr]: http://dahl.byu.edu/software/jvmr/
[rJython]: http://cran.r-project.org/web/packages/rJython/index.html
[rPython]: http://cran.r-project.org/web/packages/rPython/index.html
[runr]: https://github.com/yihui/runr
[RJulia]: https://github.com/armgong/RJulia
[RinRuby]: https://sites.google.com/a/ddahl.org/rinruby-users/
[R.matlab]: http://cran.r-project.org/web/packages/R.matlab/index.html
[RcppOctave]: https://github.com/qinwf/awesome-R/blob/master/RcppOctave
[RSPerl]: http://www.omegahat.org/RSPerl/
[RODBC]: http://cran.r-project.org/web/packages/RODBC/
[DBI]: https://github.com/rstats-db/DBI
[RMySQL]: http://cran.r-project.org/web/packages/RMySQL/
[ROracle]: http://cran.r-project.org/web/packages/ROracle/index.html
[RPostgreSQL]: https://code.google.com/p/rpostgresql/
[RSQLite]: http://cran.r-project.org/web/packages/RSQLite/
[RJDBC]: http://cran.r-project.org/web/packages/RJDBC/
[rmongodb]: https://github.com/gerald-lindsly/rmongodb
[rredis]: http://cran.r-project.org/web/packages/rredis/
[RCassandra]: http://cran.r-project.org/web/packages/RCassandra/index.html
[RHive]: https://github.com/nexr/RHive
[h2o]: http://cran.r-project.org/web/packages/h2o/index.html
[Clever Algorithms For Machine Learning]: https://github.com/jbrownlee/CleverAlgorithmsMachineLearning
[Machine Learning For Hackers]: https://github.com/johnmyleswhite/ML_for_Hackers
[rpart]: http://cran.r-project.org/web/packages/rpart/index.html
[randomForest]: http://cran.r-project.org/web/packages/randomForest/index.html
[lasso2]: http://cran.r-project.org/web/packages/lasso2/index.html
[gbm]: http://cran.r-project.org/web/packages/gbm/index.html
[e1071]: http://cran.r-project.org/web/packages/e1071/index.html
[tgp]: http://cran.r-project.org/web/packages/tgp/index.html
[rgp]: http://cran.r-project.org/web/packages/rgp/index.html
[arules]: http://cran.r-project.org/web/packages/arules/index.html
[frbs]: http://cran.r-project.org/web/packages/frbs/index.html
[rattle]: http://cran.r-project.org/web/packages/rattle/index.html
[ahaz]: http://cran.r-project.org/web/packages/ahaz/index.html
[bigrf]: http://cran.r-project.org/web/packages/bigrf/index.html
[bigRR]: http://cran.r-project.org/web/packages/bigRR/index.html
[bmrm]: http://cran.r-project.org/web/packages/bmrm/index.html
[Boruta]: http://cran.r-project.org/web/packages/Boruta/index.html
[bst]: http://cran.r-project.org/web/packages/bst/index.html
[C50]: http://cran.r-project.org/web/packages/C50/index.html
[caret]: http://cran.r-project.org/web/packages/caret/index.html
[CORElearn]: http://cran.r-project.org/web/packages/CORElearn/index.html
[CoxBoost]: http://cran.r-project.org/web/packages/CoxBoost/index.html
[Cubist]: http://cran.r-project.org/web/packages/Cubist/index.html
[earth]: http://cran.r-project.org/web/packages/earth/index.html
[elasticnet]: http://cran.r-project.org/web/packages/elasticnet/index.html
[ElemStatLearn]: http://cran.r-project.org/web/packages/ElemStatLearn/index.html
[evtree]: http://cran.r-project.org/web/packages/evtree/index.html
[GAMBoost]: http://cran.r-project.org/web/packages/GAMBoost/index.html
[gamboostLSS]: http://cran.r-project.org/web/packages/gamboostLSS/index.html
[glmnet]: http://cran.r-project.org/web/packages/glmnet/index.html
[glmpath]: http://cran.r-project.org/web/packages/glmpath/index.html
[GMMBoost]: http://cran.r-project.org/web/packages/GMMBoost/index.html
[grplasso]: http://cran.r-project.org/web/packages/grplasso/index.html
[grpreg]: http://cran.r-project.org/web/packages/grpreg/index.html
[hda]: http://cran.r-project.org/web/packages/hda/index.html
[ipred]: http://cran.r-project.org/web/packages/ipred/index.html
[kernlab]: http://cran.r-project.org/web/packages/kernlab/index.html
[klaR]: http://cran.r-project.org/web/packages/klaR/index.html
[lars]: http://cran.r-project.org/web/packages/lars/index.html
[LiblineaR]: http://cran.r-project.org/web/packages/LiblineaR/index.html
[LogicReg]: http://cran.r-project.org/web/packages/LogicReg/index.html
[maptree]: http://cran.r-project.org/web/packages/maptree/index.html
[mboost]: http://cran.r-project.org/web/packages/mboost/index.html
[mvpart]: http://cran.r-project.org/web/packages/mvpart/index.html
[ncvreg]: http://cran.r-project.org/web/packages/ncvreg/index.html
[nnet]: http://cran.r-project.org/web/packages/nnet/index.html
[oblique.tree]: http://cran.r-project.org/web/packages/oblique.tree/index.html
[pamr]: http://cran.r-project.org/web/packages/pamr/index.html
[party]: http://cran.r-project.org/web/packages/party/index.html
[partykit]: http://cran.r-project.org/web/packages/partykit/index.html
[penalized]: http://cran.r-project.org/web/packages/penalized/index.html
[penalizedLDA]: http://cran.r-project.org/web/packages/penalizedLDA/index.html
[penalizedSVM]: http://cran.r-project.org/web/packages/penalizedSVM/index.html
[quantregForest]: http://cran.r-project.org/web/packages/quantregForest/index.html
[randomForestSRC]: http://cran.r-project.org/web/packages/randomForestSRC/index.html
[rda]: http://cran.r-project.org/web/packages/rda/index.html
[rdetools]: http://cran.r-project.org/web/packages/rdetools/index.html
[REEMtree]: http://cran.r-project.org/web/packages/REEMtree/index.html
[relaxo]: http://cran.r-project.org/web/packages/relaxo/index.html
[rgenoud]: http://cran.r-project.org/web/packages/rgenoud/index.html
[Rmalschains]: http://cran.r-project.org/web/packages/Rmalschains/index.html
[rminer]: http://cran.r-project.org/web/packages/rminer/index.html
[ROCR]: http://cran.r-project.org/web/packages/ROCR/index.html
[RoughSets]: http://cran.r-project.org/web/packages/RoughSets/index.html
[RPMM]: http://cran.r-project.org/web/packages/RPMM/index.html
[RSNNS]: http://cran.r-project.org/web/packages/RSNNS/index.html
[RWeka]: http://cran.r-project.org/web/packages/RWeka/index.html
[RXshrink]: http://cran.r-project.org/web/packages/RXshrink/index.html
[sda]: http://cran.r-project.org/web/packages/sda/index.html
[SDDA]: http://cran.r-project.org/web/packages/SDDA/index.html
[svmpath]: http://cran.r-project.org/web/packages/svmpath/index.html
[tree]: http://cran.r-project.org/web/packages/tree/index.html
[varSelRF]: http://cran.r-project.org/web/packages/varSelRF/index.html
[caret 1]: http://caret.r-forge.r-project.org/
[SuperLearner]: https://github.com/ecpolley/SuperLearner
[subsemble]: http://cran.r-project.org/web/packages/subsemble/index.html
[Introduction to Statistical Learning]: http://www-bcf.usc.edu/~gareth/ISL/
[tm]: http://cran.r-project.org/web/packages/tm/index.html
[openNLP]: http://cran.r-project.org/web/packages/openNLP/index.html
[koRpus]: http://cran.r-project.org/web/packages/koRpus/index.html
[zipfR]: http://cran.r-project.org/web/packages/zipfR/index.html
[tmcn]: http://jliblog.com/app/tmcn
[rmmseg4j]: http://cran.r-project.org/web/packages/rmmseg4j/index.html
[Rwordseg]: http://jliblog.com/app/rwordseg
[coda]: http://cran.r-project.org/web/packages/coda/index.html
[mcmc]: http://cran.r-project.org/web/packages/mcmc/index.html
[MCMCpack]: http://mcmcpack.berkeley.edu/
[R2WinBUGS]: http://cran.r-project.org/web/packages/R2WinBUGS/index.html
[BRugs]: http://cran.r-project.org/web/packages/BRugs/index.html
[quantmod]: http://www.quantmod.com/
[TTR]: http://cran.r-project.org/web/packages/TTR/index.html
[PerformanceAnalytics]: http://cran.r-project.org/web/packages/PerformanceAnalytics/index.html
[zoo]: http://cran.r-project.org/web/packages/zoo/index.html
[xts]: http://cran.r-project.org/web/packages/xts/index.html
[tseries]: http://cran.r-project.org/web/packages/tseries/index.html
[fAssets]: http://cran.r-project.org/web/packages/fAssets/index.html
[Bioconductor]: http://www.bioconductor.org/
[genetics]: http://cran.r-project.org/web/packages/genetics/index.html
[gap]: http://cran.r-project.org/web/packages/gap/index.html
[ape]: http://cran.r-project.org/web/packages/ape/index.html
[devtools]: https://github.com/hadley/devtools
[testthat]: https://github.com/hadley/testthat
[R6]: https://github.com/wch/R6
[pryr]: https://github.com/hadley/pryr
[roxygen]: https://github.com/klutometis/roxygen
[lineprof]: https://github.com/hadley/lineprof
[packrat]: https://github.com/rstudio/packrat
[installr]: https://github.com/talgalili/installr/
[renjin]: http://www.renjin.org/
[pqR]: http://www.pqr-project.org/
[fastR]: https://bitbucket.org/allr/fastr/wiki/Home
[riposte]: https://github.com/jtalbot/riposte
[TERR]: http://spotfire.tibco.com/discover-spotfire/what-does-spotfire-do/predictive-analytics/tibco-enterprise-runtime-for-r-terr
[RRE]: http://www.revolutionanalytics.com/
[CXXR]: https://www.cs.kent.ac.uk/projects/cxxr/
[R-project]: http://www.r-project.org/
[R Bloggers]: http://www.r-bloggers.com/
[DataCamp]: https://www.datacamp.com/
[Quick-R]: http://www.statmethods.net/
[Advanced R]: http://adv-r.had.co.nz/
[CRAN Task Views]: http://cran.r-project.org/web/views/
[The Art of R Programming]: http://shop.oreilly.com/product/9781593273842.do
[R in Action]: http://www.manning.com/kabacoff2/
[Use R]: http://www.springer.com/series/6991?detailsPage=titles
[R_Reference_Card_2.0]: http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf
[Data Mining Refcard]: http://www.rdatamining.com/docs/R-refcard-data-mining.pdf
[Regression Analysis Refcard]: http://cran.r-project.org/doc/contrib/Ricci-refcard-regression.pdf
[Reference Card for ESS]: http://ess.r-project.org/refcard.pdf
[R Markdown Cheat sheet]: http://shiny.rstudio.com/images/rm-cheatsheet.pdf.zip
[Shiny Cheat sheet]: http://shiny.rstudio.com/images/cheatsheet.pdf.zip
[awesome-awesomeness]: https://github.com/bayandin/awesome-awesomeness
[lists]: https://github.com/jnv/lists
[http_www.open-open.com_lib_view_home_1413446023903]: http://www.open-open.com/lib/view/home/1413446023903