Scientific software R. Programming language and applications

CreateSpace Independent Publishing Platform, 2016. — 278 p. — ISBN: 1534798161, 9781534798168R is a language and programming environment for statistical analysis and graphic. It is a project of free software , a result of the implementation GNU classic scientific language S-plus. R and S-plus are probably the two languages most commonly used in research by community statistics, is also very popular in the field of the biomedical research , the bioinformatics and the financial mathematics . This contributes to the possibility of charging different libraries or packages for specific purposes of calculation or graph. is available for the operating systems Windows , Macintosh , Unix and GNU/Linux . R provides a wide range of statistical tools (models linear and non-linear , statistical tests , analysis of time series , algorithms of classification and clustering , etc.) and graphic. Like S-Plus, it's a programming language, allowing users to extend it by defining your own functions. In fact, most of the functions of R are written in the same R, although algorithms for computationally demanding is possible to develop libraries in C , C++ or Fortran that are loaded dynamically. Advanced users can also manipulate R objects directly from code developed in C. R also can spread through packages developed by its community of users. R is part of a collaborative and open project. Your users can publish packages that extend its basic configuration. Given the huge number of new packages, these have been organized in views (or themes) , which allow you to group them according to their nature and function. For example, there are groups of related packages with Bayesian statistics , Econometrics , time series , etc. R, like S plus, can be considered an object oriented programming language. In addition, R can be integrated with different databases and there are libraries that facilitate its use from programming languages interpreted as Perl and Python . R also has its own format for the documentation based on LaTeX . Another feature of R is its graphical capability, which allows you to generate high-quality graphics. R can also be used as a tool of numerical calculation , field in which it can be as effective as other specific tools such as GNU Octave and its commercial equivalent, MatLAB.