R-Cran 2.9.1 & Rkward 0.5.1

rlogoR-Cran 2.9.1 & Rkward 0.5.1 per Mandriva Linux 2009.1
R is a language and environment for statistical computing and graphics.

It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. 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.

One of R's strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.

R is available as Free Software under the terms of the Free Software Foundation's GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.



                CHANGES IN R VERSION 2.9.1


o New function anyDuplicated(x) returns 0 (= FALSE) or the index
of the first duplicated entry of x.

o matplot(), matlines() and matpoints() now also obey a 'lend'
argument, determining line end styles. (Wish of PR#13619).

o bw.SJ(), bw.bcv() and bw.ucv() now gain an optional 'tol'
argument allowing more accurate estimates.

o new.packages() no longer regards packages with the same name
as a member of an installed bundle as 'new' (this is now
consistent with the dependency checks in install.packages()).

It no longer reports on partially installed bundles (since
members can be updated individually if a bundle is unbundled).

o old.packages() and hence updates.packages() will look for
updates to members of package bundles before updates to the
whole bundle: this allow bundles to be split and installations

o nlminb() gives better non-convergence messages in some cases.

o S3 method dispatch will support S4 class inheritance for S3
methods, for primitives and via UseMethod(), if the argument
S3methods=TRUE is given to setClass(). S4 method dispatch
will use S3 per-object inheritance if S3Class() is set on the
object. See ?Methods and the paper referenced there.

o R CMD INSTALL is more tolerant of (malformed) packages with a
'man' directory but no validly named .Rd files.

o R CMD check now reports where options are used that cause some
of the checks to be skipped.

o RSiteSearch has been updated to be consistent with the new
layout of the search site itself, which now includes separate
options for vignettes, views, and r-sig-mixed-models, as well
as changed names for r-help. (Contributed by Jonathan Baron.)

o That R CMD check makes use of a
<pkg>/tests/Examples/<pkg>-Ex.Rout.save file as a reference
result is now documented in 'Writing R Extensions'.


o print.atomic() (defunct since 1.9.0) has been removed since it
caused confusion for an S4 class union "atomic".

o png(type="cairo1") is deprecated -- it was only needed for
platforms with 1.0 <= cairo < 1.2.

More information in


RKWard 0.5.1

But if you don't feel very confortable with R language via terminal, you can use a GUI program based in R language, its name is Rkward and now is in his stable version for KDE 4.

Rkward replace SPSS, is GPL V2 license, and you can working with enormous quantity of R-Applications from Rkward repository, it is very intuitive and useful.

Rkward is nearly compatible with your SPSS works.

Rkward is more powerful than SPSS because R language is more powerful than SPSS language, because it uses lappack fortran libraries, the most complete and optimized libraries for maths and statistics.










Porting: Crislosi

Build: Crislosi

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