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Now and Then examines how promising open source software fared over the years. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, … and graphical techniques, and is highly extensible.
The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes. R, like S, is designed around a true computer language, and it allows users to add additional functionality by defining new functions. Much of the system is itself written in the R dialect of S, which makes it easy for users to follow the algorithmic choices made.
Advanced users can write C code to manipulate R objects directly. Many users think of R as a statistics system.
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