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R for Windows 4.1.1 / 4.2.0 r81086 Pre-release (GPLv2)

1 year ago 52

This programming language provides you with a development environment to create applications for data analysis and statistical computing

What's new in R for Windows 4.1.1:

NEW FEATURES: require(pkg, quietly = TRUE) is quieter and in particular does not warn if the package is not found. DEPRECATED AND DEFUNCT: Use of ftp:// URIs should be regarded as deprecated, with on-going support confined to method = "libcurl" and not routinely

Read the full changelog

R for Windows is a development tool prefered by the programmers who need to create software for data analysis purposes. The package includes the programming language components and other tools required for building the desired application.

Each programming language is built for a certain purpose and includes optimizations for a certain field. The R language is designed to create applications that easily manage and visualize statistical data.

In order to analyze data, R includes support for linear and nonlinear modelling, classifications and other specific tools. It can also be used for generating graphical representations of the input data.

The main tool for building an application is the integrated development environment which can be used for editing code and testing the output. It provides you with a graphical interface where you can access the console, create scripts and install additional packages.

As most data analysis applications need visualization features, R includes several graphical facilities designed to display the common statistical graphs. You can also use the commands to create customized graphs suitable for the type of data that needs to be analyzed.

Although you need programming experience to create applications, the package includes multiple samples which can help you get started. The details about a certain function can easily be accessed in the console or by opening the HTML help in any Internet browser.

One of the advantages of the R language is the ability to extend its features by creating packages. The experienced programmers can create custom packages for their projects by using the guide included in the documentation.

Overall, R for Windows provides a flexible development environment which can help you build data analysis tools for your needs.

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Data manipulation Statistical computation Data analysis Statistics Computation Analysis Analyzer

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