Have you
heard R before? I am sure you know it well as a character in English, but for a
very important statistical programming language, you may don’t know it very
much. R is a free software programming language and software environment for
statistical computing and graphics. [1]
Do you still
remember my open source blog? If you have read it, you must know R is becoming
the most popular R is becoming the most popular worldwide applied statistical
language. It is widely used among statisticians and data miners for developing
statistical software and data analysis. R could not only help academics to
solve most challenging problems in fields
ranging from computational biology to quantitative finance, but also to train
their students in these fields. The most amazing part of R is it enable
advanced user to manipulate R objects directly with C, C++, or Java code.
We have a
word in statistics: R could do almost everything for you. R provides a wide
variety of statistical and graphical techniques, including linear and nonlinear
modeling, classical statistical tests, time-series analysis, classification,
clustering, and others. [2] R has similar syntax as language C, and it is also
a functional programming language. It has strong compatibility with APL and
Lisp. In particular, it allows computing on the language. This makes it
possible to input expression.
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