R (programming language)
programming language for statistical analysis From Wikipedia, the free encyclopedia
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R is a programming language and free software environment for statistics.[6][7][8][9][10][11] R is a language built for a specific purpose. It is strictly designed for statistical analysis. The algorithms for many statistical models are devised in R. Precisely R is the language of Statistical Analyzers. It’s an open source and the best suite for the statisticians to develop statistical softwares.
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Usage in other areas
The R language was originally made for statistics. But today, it is also used in many scientific fields including ecology.[12][13]
Development history
A list of changes in R releases is maintained in various "news" files at CRAN (Comprehensive R Archive Network).[14] Some highlights are listed below for several major releases.
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Communities
R has local communities worldwide for users to share ideas and learn.[21][22]
There are a growing number of R events bringing its users together, such as conferences (e.g. useR!, WhyR?, conectaR, SatRdays)[23][24] and other meetups.[25]
useR! conferences
The official annual gathering of R users is called "useR!".[26] The first such event was useR! 2004 in May 2004, Vienna, Austria.[27] After skipping 2005, the useR! conference has been held annually.[28] Subsequent conferences have included:[26]
- useR! 2006, Vienna, Austria
- useR! 2007, Ames, Iowa, USA
- useR! 2008, Dortmund, Germany
- useR! 2009, Rennes, France
- useR! 2010, Gaithersburg, Maryland, USA
- useR! 2011, Coventry, United Kingdom
- useR! 2012, Nashville, Tennessee, USA
- useR! 2013, Albacete, Spain
- useR! 2014, Los Angeles, California, USA
- useR! 2015, Aalborg, Denmark
- useR! 2016, Stanford, California, USA
- useR! 2017, Brussels, Belgium
- useR! 2018, Brisbane, Australia
- useR! 2019, Toulouse, France
Future conferences planned are as follows:[26][29]
- useR! 2020, St. Louis, Missouri, USA (Canceled)
- useR! 2021, Zurich, Switzerland
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The R Journal
The R Journal is the open access refereed journal of the R project. It features articles on the use and development of the R language.
Basic syntax
The following examples illustrate the basic syntax of the language and use of the command-line interface.
In R, the generally preferred[30] assignment operator is an arrow made from two characters <-. Although = can be used instead.[31]
> x <- 1:6 # Create vector.
> y <- x^2 # Create vector by formula.
> print(y) # Print the vector’s contents.
[1] 1 4 9 16 25 36
> mean(y) # Arithmetic mean of vector.
[1] 15.16667
> var(y) # Sample variance of vector.
[1] 178.9667
> model <- lm(y ~ x) # Linear regression model y = A + B * x.
> print(model) # Print the model’s results.
Call:
lm(formula = y ~ x)
Coefficients:
(Intercept) x
-9.333 7.000
> summary(model) # Display an in-depth summary of the model.
Call:
lm(formula = y ~ x)
Residuals:
1 2 3 4 5 6
3.3333 -0.6667 -2.6667 -2.6667 -0.6667 3.3333
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -9.3333 2.8441 -3.282 0.030453 *
x 7.0000 0.7303 9.585 0.000662 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 3.055 on 4 degrees of freedom
Multiple R-squared: 0.9583, Adjusted R-squared: 0.9478
F-statistic: 91.88 on 1 and 4 DF, p-value: 0.000662
> par(mfrow = c(2, 2)) # Create a 2 by 2 layout for figures.
> plot(model) # Output diagnostic plots of the model.
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References
Other websites
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