Difference between revisions of "Software:R"
(→Introduction) |
|||
Line 1: | Line 1: | ||
== Introduction == | == Introduction == | ||
− | R is a language and environment for statistical computing and graphics. It provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. | + | R is a language and environment for statistical computing and graphics. It provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. Although R is not well-suited for HPC cluster, functionality and flexibility for data handling and analysis make it a essential tool for researcher from wide range of scientific discipline. In addition, R provide a large repository of user built packages suits for different range of applications. |
− | + | ||
+ | You can run your R script from our Rstudio or through a batch script on compute nodes. Rstudio(https://login.cac.queensu.ca/rstudio/) provide our user with a IDE to develop and run your program on a webserver. But it is constrained in term of the available packages and the compute resource. | ||
== Starting R console == | == Starting R console == | ||
== Installing R packages == | == Installing R packages == |
Revision as of 20:02, 22 March 2022
Introduction
R is a language and environment for statistical computing and graphics. It provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible. Although R is not well-suited for HPC cluster, functionality and flexibility for data handling and analysis make it a essential tool for researcher from wide range of scientific discipline. In addition, R provide a large repository of user built packages suits for different range of applications.
You can run your R script from our Rstudio or through a batch script on compute nodes. Rstudio(https://login.cac.queensu.ca/rstudio/) provide our user with a IDE to develop and run your program on a webserver. But it is constrained in term of the available packages and the compute resource.