R project for statistical computing

The R project

R is a comprehensive  language and environment for statistical computing and graphical programming. This link redirect you to the R-project official web page.

Quick-R, accessing the power of R

The following links enable you to use the material available at the Quick-R web page.

Importing Data into R. Importing data into R is fairly simple. This link will help you to learn how to do it in a few minutes.

Exporting Data from R. There are numerous methods for exporting R objects into other formats. This link will show to you five simple ways to do it.

Missing Data in R. Missing values are represented in R by the symbol NA (not available), whereas impossible values (e.g., dividing by zero) are represented by the symbol NaN (not a number). This link will illustrate the variety of function available in R to handle missing data.

Matrix algebra with R. Efficient implementation of the main linear algebra methods might be found in R. This link provides cover operators and functions specifically suited to linear algebra.

Open sourse softwares for the analysis of complex networks

Social network analysis software facilitates statistical analysis of social networks, by describing features either through numerical or visual representation. Some of them can perform predictive analysis, either using network phenomena such as a tie to predict individual level outcomes or using individual-level phenomena to predict network outcomes such as the formation of a tie, or using network phenomena to predict other network phenomena, such as using a triad formation to predict community structure. Network analysis software generally consists of either packages based on graphical user interfaces (GUIs), or packages built for scripting/programming languages. Widely used and well-documented GUI packages include NetMiner, UCINet, Pajek (freeware), GUESS, ORA, Cytoscape, Gephi and muxViz (opensource). The following links allow you to directly connect to the pages for downloading the aforementioned packages of social network analysis based on GUIs.

Igraph is a collection of network analysis tools with the emphasis on efficiency, portability and ease of use. igraph is open source and free. igraph can be programmed in R, Python and C/C++

	Ucinet 6, a friendly software package for the analysis of complex network Windows, developed by Lin Freeman, Martin Everett and Steve Borgatti.
	Cytoscape, a software platform for visualizing complex networks, with several plugins available for bioinformatics, social networks, microeconomics, etc.
	Siena, a computer program for the statistical analysis of network data, with the focus on big social networks and random graphs.
	Stocnet, an advanced software for statistical analysis of complex networks, built in 1998 by Frans Stokman, Tom Snijders and Marijtje van Duijn.
	Gephi, an interactive platform for Windows, Linux and Mac OS X, which allows working with all kinds of networks and complex systems, dynamic and hierarchical graphs.
	Pajek, a software packet for Windows, developed by Vladimir Batagelj, which allow the analysis and visualization of large networks.
	SocNetV, a friendly tool for the analysis and visualization of Social Networks, allowing the construction of networks with a few clicks.

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