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The R Commander: A Basic-Statistics Graphical User Interface to R

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  • Fox, John

Abstract

Unlike S-PLUS, R does not incorporate a statistical graphical user interface (GUI), but it does include tools for building GUIs. Based on the tcltk package (which furnishes an interface to the Tcl/Tk GUI toolkit), the Rcmdr package provides a basic-statistics graphical user interface to R called the "R Commander." The design objectives of the R Commander were as follows: to support, through an easy-to-use, extensible, cross-platform GUI, the statistical functionality required for a basic-statistics course (though its current functionality has grown to include support for linear and generalized-linear models, and other more advanced features); to make it relatively difficult to do unreasonable things; and to render visible the relationship between choices made in the GUI and the R commands that they generate. The R Commander uses a simple and familiar menu/dialog-box interface. Top-level menus include File, Edit, Data, Statistics, Graphs, Models, Distributions, Tools, and Help, with the complete menu tree given in the paper. Each dialog box includes a Help button, which leads to a relevant help page. Menu and dialog-box selections generate R commands, which are recorded in a script window and are echoed, along with output, to an output window. The script window also provides the ability to edit, enter, and re-execute commands. Error messages, warnings, and some other information appear in a separate messages window. Data sets in the R Commander are simply R data frames, and can be read from attached packages or imported from files. Although several data frames may reside in memory, only one is "active" at any given time. There may also be an active statistical model (e.g., an R lm or glm ob ject). The purpose of this paper is to introduce and describe the use of the R Commander GUI; to describe the design and development of the R Commander; and to explain how the R Commander GUI can be extended. The second part of the paper (following a brief introduction) can serve as an introductory guide for students who will use the R Commander.

Suggested Citation

  • Fox, John, 2005. "The R Commander: A Basic-Statistics Graphical User Interface to R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i09).
    • Handle: RePEc:jss:jstsof:v:014:i09
    DOI: http://hdl.handle.net/10.18637/jss.v014.i09
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    References listed on IDEAS

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    1. Fox, John, 2003. "Effect Displays in R for Generalised Linear Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 8(i15).
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    Cited by:

    1. Nicoleta Caragea & Ana Maria Dobre & Antoniade Ciprian Alexandru, 2013. "Profile Of Migrants In Romania – A Statistical Analysis Using "R"," Working papers 04, Ecological University of Bucharest, Department of Economics.
    2. Lopez-de-Lacalle, Javier, 2006. "The R-computing language: Potential for Asian economists," Journal of Asian Economics, Elsevier, vol. 17(6), pages 1066-1081, December.
    3. Bašta, Milan & Helman, Karel, 2013. "Scale-specific importance of weather variables for explanation of variations of electricity consumption: The case of Prague, Czech Republic," Energy Economics, Elsevier, vol. 40(C), pages 503-514.
    4. Nicoleta CARAGEA & Antoniade Ciprian ALEXANDRU & Ana Maria DOBRE, 2014. "Pattern Of Financial Savings In A Romanian Bank – A Statistical Analysis," Post-Crisis Trends - Working papers 02, Ecological University of Bucharest, Department of Economics.
    5. Aizaki, Hideo & Fogarty, James, 2023. "R packages and tutorial for case 1 best–worst scaling," Journal of choice modelling, Elsevier, vol. 46(C).
    6. Rödiger, Stefan & Friedrichsmeier, Thomas & Kapat, Prasenjit & Michalke, Meik, 2012. "RKWard: A Comprehensive Graphical User Interface and Integrated Development Environment for Statistical Analysis with R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 49(i09).
    7. Jiří Sedláček, 2013. "Using R in Finance [Využití R v oblasti financí]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2013(4), pages 145-163.
    8. Conrad, Yvonne & Fohrer, Nicola, 2016. "Simulating impacts of silage maize (Zea mays) in monoculture and undersown with annual grass (Lolium perenne L.) on the soil water balance in a sandy-humic soil in Northwest Germany," Agricultural Water Management, Elsevier, vol. 178(C), pages 52-65.
    9. Bastiaan Quast & Victor Kummritz, 2015. "Decompr: Global Value Chain Decomposition In R," CTEI Working Papers series 01-2015, Centre for Trade and Economic Integration, The Graduate Institute.

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