R Programming

---

• R Basics
  • Introduction
  • Sample Session
  • Manage your workspace
  • Settings and Installation
  • Documentation
  • Control Structures
  • Working with functions
  • Debugging
  • Using C or Fortran
  • Utilities
  • Estimation utilities
  • Packages
• Data Management
  • Data types
  • Working with data frames
  • Importing and exporting data
  • Text Processing
  • Times and Dates
• Graphics
  • Grammar of graphics
• Publication quality output
• Descriptive Statistics
• Mathematics
  • Optimization
  • Probability Distributions
  • Random Number Generation
• Statistical Core Methods
  • Maximum Likelihood
  • Method of Moments
  • Bayesian Methods
  • Bootstrap
  • Multiple Imputation
  • Nonparametric Methods
• Regression Models
  • Linear Models
  • Quantile Regression
  • Binomial Models
  • Multinomial Models
  • Tobit And Selection Models
  • Count Data Models
  • Duration Analysis
• Time Series
• Factor Analysis
• Classification
  • Ordination
  • Clustering
• Network Analysis
• High Performance Computing
  • Profiling R code
  • Parallel computing with R
• Appendix
  • Sources
  • Index

---

edit this box

For some tasks, R can be slow. In that case, it is possible to write a program in C or Fortran and to use it from R. This page is for advanced programmers only.

• See wikiversity Connecting Fortran and R
• Link C with R

References