R- Programming and its base:
When a user
thinks for graphics and statistical computing -
R is a correc t platform to manage such functions. R- provides bestenviroment for such functions. R- is a project executed by GNU and it is much relevant to the S language . S language was produced at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be defined as a varied implementation of S.
We can find some major differences, but most of the codes written for S can run unchanged under R.
R offers a wide range and choices of statistical and graphical techniques like linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …), and is highly extensible. If a user wants to do research in the methods of statistics then often the use of the S language is used. And in this activity , R supports as an Open Source way.
The strength and advantage of R is the comfort and ease of programming with which well-designed publication-quality plots can be developed, which includes mathematical signs and formulae wherever they are needed. To make the minor design choice in the graphics, defaults are needed to be taken care of it. But user has a full control over it.
To develop the software in statistics and to analyze the data , R language is widely used. R programming language is supported by R foundation and is the base for user in statistical computing and graphics.
The R environment
R is a mixed amalgamation of
facilities of softwares like display of graphics , calculation of data and
other manipulation of datas . In short you can consider R as an integrated
format of all this activities. Below are
the components and characteristics that are included in R environment:
- Data can handled effectively,
- Storage capacity and characteristics
- For array calculations with precised
matrices , a pannel of operators are available.
- For Data analysis : Huge , solid and
amalagated coolection og tools are available.
- For graphical analysis or to display it
on either screen or on hardcopy , many graphical facilites are available
in R.
- a well-developed, easy and effective
programming language which has inclusions of conditionals, loops,
user-defined recursive functions and input and output facilities.
The purpose to use the term
“environment” is to distinguish it as a fully planned and coherent system,
rather than an incremental accretion of very specific and unmodified tools, as
is usually the case with most of the other data analysis software.
Same as S , R is also sculptured
around a correct and genuine computer language, and it permits users to add
additional functionality by defining new functions. Much of the system is
itself written in the R dialect of S, due to which the users get much convenience to
move on the path of the algorithmic choices made.
Many users think of R as a statistics
system. We prefer to think of it of an environment within which statistical
techniques are implemented. R can be extended (easily) via packages.
There are about eight packages supplied with the R distribution and a lot more
are available through the CRAN family of Internet sites covering a very wide
range of modern statistics.
LaTeX documentation format is
available in R , and it has been used to provide a comprehensive documentation,
in both the formats i.e. on-line in a variety
of formats and in hardcopy.
