From the marvelous lovely Journal of Statistical Software, ignored by mainstream corporatia, but beloved to academia. here is one more interesting and very timely paper.
Can be used to grade stdudents homework, catch terrorists as in plagiarists , search engine spam linkers. Enjoy!
I am hoping to put this on my pre-ordered or Amazon Wish list. The book the common people who wanted to do data mining with , but were unable to ask aloud they didnt know much. It is written by the seminal Australian authority on data mining Dr Graham Williams whom I interviewed here at https://decisionstats.com/2009/01/13/interview-dr-graham-williams/
Data Mining for the masses using an ergonomically designed Graphical User Interface.
Thank you Springer. Thank you Dr Graham Williams
http://www.springer.com/statistics/physical+%26+information+science/book/978-1-4419-9889-7
The Art of Excavating Data for Knowledge Discovery
Series: Use R
Williams, Graham
1st Edition., 2011, XX, 409 p. 150 illus. in color.
Softcover, ISBN 978-1-4419-9889-7
Due: August 29, 2011
Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms.
Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing.
The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings.
Content Level » Research
Keywords » Data mining
Related subjects » Physical & Information Science
Related- https://decisionstats.com/2009/01/13/interview-dr-graham-williams/
Based on the official email from them, God bless the merry coders at Revo-
Revolution Analytics has just released Revolution R Enterprise 4.3 for 32-bit and 64-bit Windows, a significant step forward in enterprise data analytics. It features an updated RevoScaleR package for scalable, fast (multicore), and extensible data analysis with R. Revolution R Enterprise 4.3 for Windows also provides R 2.12.2, and includes an enhanced R Productivity Environment (RPE), a full-featured integrated development environment with visual debugging capabilities. Also available is an updated Windows release of our deployment server solution, RevoDeployR 1.2, designed to help you deliver R analytics via the Web.
As a registered user of the Academic version of Revolution R Enterprise for Windows, you can take advantage of these improvements by downloading and installing Revolution R Enterprise 4.3 today. You can install Revolution R Enterprise 4.3 side-by-side with your existing Revolution R Enterprise installations; there is no need to uninstall previous versions.
Marry Big Data Analytics to High Performance Computing, and you get the buzzword of this season- High Performance Analytics.
It basically consists of Parallelized code to run in parallel on custom hardware, in -database analytics for speed, and cloud computing /high performance computing environments. On an operational level, it consists of software (as in analytics) partnering with software (as in databases, Map reduce, Hadoop) plus some hardware (HP or IBM mostly). It is considered a high margin , highly profitable, business with small number of deals compared to say desktop licenses.
As per HPC Wire- which is a great tool/newsletter to keep updated on HPC , SAS Institute has been busy on this front partnering with EMC Greenplum and TeraData (who also acquired SAS Partner AsterData to gain a much needed foot in the MR/SQL space) Continue reading “High Performance Analytics”
The newest version of R is now available for download. R 2.13 is ready !!
http://cran.at.r-project.org/bin/windows/base/CHANGES.R-2.13.0.html
win_iconv has been updated: this version has a change in the behaviour with BOMs on UTF-16 and UTF-32 files – it removes BOMs when reading and adds them when writing. (This is consistent with Microsoft applications, but Unix versions of iconv usually ignore them.)
options("browser") and options("pdfviewer") are now set from environment variables R_BROWSER and R_PDFVIEWER respectively (as on a Unix-alike). A value of "false" suppresses display (even if there is no false.exe present on the path).
options("install.lock") is set to TRUE, binary package installs are protected against failure similar to the way source package installs are protected.
file.exists() and unlink() have more support for files > 2GB.
R.exe in ‘R_HOME/bin/i386,x64/bin’ now support options such as R --vanilla CMD: there is no comparable interface for ‘Rcmd.exe’.
Rcmd.exe).
Rgui has a new menu item for the PDF ‘Sweave User Manual’.
unzip().
JPEGDIR to that value in ‘MkRules.local’.
Support for jpeg-6b has been removed.
casinh function on the branch cuts.windows(). The symptom was the occasional raster image not being drawn, especially when drawing multiple raster images in a single expression. Thanks to Michael Sumner for report and testing.Tonnes of changes!!
http://cran.at.r-project.org/src/base/NEWS
CHANGES IN R VERSION 2.13.0:
SIGNIFICANT USER-VISIBLE CHANGES:
• replicate() (by default) and vapply() (always) now return a
higher-dimensional array instead of a matrix in the case where
the inner function value is an array of dimension >= 2.
• Printing and formatting of floating point numbers is now using
the correct number of digits, where it previously rarely differed
by a few digits. (See “scientific†entry below.) This affects
_many_ *.Rout.save checks in packages.
NEW FEATURES:
• normalizePath() has been moved to the base package (from utils):
this is so it can be used by library() and friends.
It now does tilde expansion.
It gains new arguments winslash (to select the separator on
Windows) and mustWork to control the action if a canonical path
cannot be found.
• The previously barely documented limit of 256 bytes on a symbol
name has been raised to 10,000 bytes (a sanity check). Long
symbol names can sometimes occur when deparsing expressions (for
example, in model.frame).
• reformulate() gains a intercept argument.
• cmdscale(add = FALSE) now uses the more common definition that
there is a representation in n-1 or less dimensions, and only
dimensions corresponding to positive eigenvalues are used.
(Avoids confusion such as PR#14397.)
• Names used by c(), unlist(), cbind() and rbind() are marked with
an encoding when this can be ascertained.
• R colours are now defined to refer to the sRGB color space.
The PDF, PostScript, and Quartz graphics devices record this
fact. X11 (and Cairo) and Windows just assume that your screen
conforms.
• system.file() gains a mustWork argument (suggestion of Bill
Dunlap).
• new.env(hash = TRUE) is now the default.
• list2env(envir = NULL) defaults to hashing (with a suitably sized
environment) for lists of more than 100 elements.
• text() gains a formula method.
• IQR() now has a type argument which is passed to quantile().
• as.vector(), as.double() etc duplicate less when they leave the
mode unchanged but remove attributes.
as.vector(mode = "any") no longer duplicates when it does not
remove attributes. This helps memory usage in matrix() and
array().
matrix() duplicates less if data is an atomic vector with
attributes such as names (but no class).
dim(x) <- NULL duplicates less if x has neither dimensions nor
names (since this operation removes names and dimnames).
• setRepositories() gains an addURLs argument.
• chisq.test() now also returns a stdres component, for
standardized residuals (which have unit variance, unlike the
Pearson residuals).
• write.table() and friends gain a fileEncoding argument, to
simplify writing files for use on other OSes (e.g. a spreadsheet
intended for Windows or Mac OS X Excel).
• Assignment expressions of the form foo::bar(x) <- y and
foo:::bar(x) <- y now work; the replacement functions used are
foo::`bar<-` and foo:::`bar<-`.
• Sys.getenv() gains a names argument so Sys.getenv(x, names =
FALSE) can replace the common idiom of as.vector(Sys.getenv()).
The default has been changed to not name a length-one result.
• Lazy loading of environments now preserves attributes and locked
status. (The locked status of bindings and active bindings are
still not preserved; this may be addressed in the future).
• options("install.lock") may be set to FALSE so that
install.packages() defaults to --no-lock installs, or (on
Windows) to TRUE so that binary installs implement locking.
• sort(partial = p) for large p now tries Shellsort if quicksort is
not appropriate and so works for non-numeric atomic vectors.
• sapply() gets a new option simplify = "array" which returns a
“higher rank†array instead of just a matrix when FUN() returns a
dim() length of two or more.
replicate() has this option set by default, and vapply() now
behaves that way internally.
• aperm() becomes S3 generic and gets a table method which
preserves the class.
• merge() and as.hclust() methods for objects of class "dendrogram"
are now provided.
• as.POSIXlt.factor() now passes ... to the character method
(suggestion of Joshua Ulrich).
• The character method of as.POSIXlt() now tries to find a format
that works for all non-NA inputs, not just the first one.
• str() now has a method for class "Date" analogous to that for
class "POSIXt".
• New function file.link() to create hard links on those file
systems (POSIX, NTFS but not FAT) that support them.
• New Summary() group method for class "ordered" implements min(),
max() and range() for ordered factors.
• mostattributes<-() now consults the "dim" attribute and not the
dim() function, making it more useful for objects (such as data
frames) from classes with methods for dim(). It also uses
attr<-() in preference to the generics name<-(), dim<-() and
dimnames<-(). (Related to PR#14469.)
• There is a new option "browserNLdisabled" to disable the use of
an empty (e.g. via the ‘Return’ key) as a synonym for c in
browser() or n under debug(). (Wish of PR#14472.)
• example() gains optional new arguments character.only and
give.lines enabling programmatic exploration.
• serialize() and unserialize() are no longer described as
‘experimental’. The interface is now regarded as stable,
although the serialization format may well change in future
releases. (serialize() has a new argument version which would
allow the current format to be written if that happens.)
New functions saveRDS() and readRDS() are public versions of the
‘internal’ functions .saveRDS() and .readRDS() made available for
general use. The dot-name versions remain available as several
package authors have made use of them, despite the documentation.
saveRDS() supports compress = "xz".
• Many functions when called with a not-open connection will now
ensure that the connection is left not-open in the event of
error. These include read.dcf(), dput(), dump(), load(),
parse(), readBin(), readChar(), readLines(), save(), writeBin(),
writeChar(), writeLines(), .readRDS(), .saveRDS() and
tools::parse_Rd(), as well as functions calling these.
• Public functions find.package() and path.package() replace the
internal dot-name versions.
• The default method for terms() now looks for a "terms" attribute
if it does not find a "terms" component, and so works for model
frames.
• httpd() handlers receive an additional argument containing the
full request headers as a raw vector (this can be used to parse
cookies, multi-part forms etc.). The recommended full signature
for handlers is therefore function(url, query, body, headers,
...).
• file.edit() gains a fileEncoding argument to specify the encoding
of the file(s).
• The format of the HTML package listings has changed. If there is
more than one library tree , a table of links to libraries is
provided at the top and bottom of the page. Where a library
contains more than 100 packages, an alphabetic index is given at
the top of the section for that library. (As a consequence,
package names are now sorted case-insensitively whatever the
locale.)
• isSeekable() now returns FALSE on connections which have
non-default encoding. Although documented to record if ‘in
principle’ the connection supports seeking, it seems safer to
report FALSE when it may not work.
• R CMD REMOVE and remove.packages() now remove file R.css when
removing all remaining packages in a library tree. (Related to
the wish of PR#14475: note that this file is no longer
installed.)
• unzip() now has a unzip argument like zip.file.extract(). This
allows an external unzip program to be used, which can be useful
to access features supported by Info-ZIP's unzip version 6 which
is now becoming more widely available.
• There is a simple zip() function, as wrapper for an external zip
command.
• bzfile() connections can now read from concatenated bzip2 files
(including files written with bzfile(open = "a")) and files
created by some other compressors (such as the example of
PR#14479).
• The primitive function c() is now of type BUILTIN.
• plot(<dendrogram>, .., nodePar=*) now obeys an optional xpd
specification (allowing clipping to be turned off completely).
• nls(algorithm="port") now shares more code with nlminb(), and is
more consistent with the other nls() algorithms in its return
value.
• xz has been updated to 5.0.1 (very minor bugfix release).
• image() has gained a logical useRaster argument allowing it to
use a bitmap raster for plotting a regular grid instead of
polygons. This can be more efficient, but may not be supported by
all devices. The default is FALSE.
• list.files()/dir() gains a new argument include.dirs() to include
directories in the listing when recursive = TRUE.
• New function list.dirs() lists all directories, (even empty
ones).
• file.copy() now (by default) copies read/write/execute
permissions on files, moderated by the current setting of
Sys.umask().
• Sys.umask() now accepts mode = NA and returns the current umask
value (visibly) without changing it.
• There is a ! method for classes "octmode" and "hexmode": this
allows xor(a, b) to work if both a and b are from one of those
classes.
• as.raster() no longer fails for vectors or matrices containing
NAs.
• New hook "before.new.plot" allows functions to be run just before
advancing the frame in plot.new, which is potentially useful for
custom figure layout implementations.
• Package tools has a new function compactPDF() to try to reduce
the size of PDF files _via_ qpdf or gs.
• tar() has a new argument extra_flags.
• dotchart() accepts more general objects x such as 1D tables which
can be coerced by as.numeric() to a numeric vector, with a
warning since that might not be appropriate.
• The previously internal function create.post() is now exported
from utils, and the documentation for bug.report() and
help.request() now refer to that for create.post().
It has a new method = "mailto" on Unix-alikes similar to that on
Windows: it invokes a default mailer via open (Mac OS X) or
xdg-open or the default browser (elsewhere).
The default for ccaddress is now getOption("ccaddress") which is
by default unset: using the username as a mailing address
nowadays rarely works as expected.
• The default for options("mailer") is now "mailto" on all
platforms.
• unlink() now does tilde-expansion (like most other file
functions).
• file.rename() now allows vector arguments (of the same length).
• The "glm" method for logLik() now returns an "nobs" attribute
(which stats4::BIC() assumed it did).
The "nls" method for logLik() gave incorrect results for zero
weights.
• There is a new generic function nobs() in package stats, to
extract from model objects a suitable value for use in BIC
calculations. An S4 generic derived from it is defined in
package stats4.
• Code for S4 reference-class methods is now examined for possible
errors in non-local assignments.
• findClasses, getGeneric, findMethods and hasMethods are revised
to deal consistently with the package= argument and be consistent
with soft namespace policy for finding objects.
• tools::Rdiff() now has the option to return not only the status
but a character vector of observed differences (which are still
by default sent to stdout).
• The startup environment variables R_ENVIRON_USER, R_ENVIRON,
R_PROFILE_USER and R_PROFILE are now treated more consistently.
In all cases an empty value is considered to be set and will stop
the default being used, and for the last two tilde expansion is
performed on the file name. (Note that setting an empty value is
probably impossible on Windows.)
• Using R --no-environ CMD, R --no-site-file CMD or R
--no-init-file CMD sets environment variables so these settings
are passed on to child R processes, notably those run by INSTALL,
check and build. R --vanilla CMD sets these three options (but
not --no-restore).
• smooth.spline() is somewhat faster. With cv=NA it allows some
leverage computations to be skipped,
• The internal (C) function scientific(), at the heart of R's
format.info(x), format(x), print(x), etc, for numeric x, has been
re-written in order to provide slightly more correct results,
fixing PR#14491, notably in border cases including when digits >=
16, thanks to substantial contributions (code and experiments)
from Petr Savicky. This affects a noticable amount of numeric
output from R.
• A new function grepRaw() has been introduced for finding subsets
of raw vectors. It supports both literal searches and regular
expressions.
• Package compiler is now provided as a standard package. See
?compiler::compile for information on how to use the compiler.
This package implements a byte code compiler for R: by default
the compiler is not used in this release. See the ‘R
Installation and Administration Manual’ for how to compile the
base and recommended packages.
• Providing an exportPattern directive in a NAMESPACE file now
causes classes to be exported according to the same pattern, for
example the default from package.skeleton() to specify all names
starting with a letter. An explicit directive to
exportClassPattern will still over-ride.
• There is an additional marked encoding "bytes" for character
strings. This is intended to be used for non-ASCII strings which
should be treated as a set of bytes, and never re-encoded as if
they were in the encoding of the currrent locale: useBytes = TRUE
is autmatically selected in functions such as writeBin(),
writeLines(), grep() and strsplit().
Only a few character operations are supported (such as substr()).
Printing, format() and cat() will represent non-ASCII bytes in
such strings by a \xab escape.
• The new function removeSource() removes the internally stored
source from a function.
• "srcref" attributes now include two additional line number
values, recording the line numbers in the order they were parsed.
• New functions have been added for source reference access:
getSrcFilename(), getSrcDirectory(), getSrcLocation() and
getSrcref().
• Sys.chmod() has an extra argument use_umask which defaults to
true and restricts the file mode by the current setting of umask.
This means that all the R functions which manipulate
file/directory permissions by default respect umask, notably R
CMD INSTALL.
• tempfile() has an extra argument fileext to create a temporary
filename with a specified extension. (Suggestion and initial
implementation by Dirk Eddelbuettel.)
There are improvements in the way Sweave() and Stangle() handle
non-ASCII vignette sources, especially in a UTF-8 locale: see
‘Writing R Extensions’ which now has a subsection on this topic.
• factanal() now returns the rotation matrix if a rotation such as
"promax" is used, and hence factor correlations are displayed.
(Wish of PR#12754.)
• The gctorture2() function provides a more refined interface to
the GC torture process. Environment variables R_GCTORTURE,
R_GCTORTURE_WAIT, and R_GCTORTURE_INHIBIT_RELEASE can also be
used to control the GC torture process.
• file.copy(from, to) no longer regards it as an error to supply a
zero-length from: it now simply does nothing.
• rstandard.glm gains a type argument which can be used to request
standardized Pearson residuals.
• A start on a Turkish translation, thanks to Murat Alkan.
• .libPaths() calls normalizePath(winslash = "/") on the paths:
this helps (usually) present them in a user-friendly form and
should detect duplicate paths accessed via different symbolic
links.
SWEAVE CHANGES:
• Sweave() has options to produce PNG and JPEG figures, and to use
a custom function to open a graphics device (see ?RweaveLatex).
(Based in part on the contribution of PR#14418.)
• The default for Sweave() is to produce only PDF figures (rather
than both EPS and PDF).
• Environment variable SWEAVE_OPTIONS can be used to supply
defaults for existing or new options to be applied after the
Sweave driver setup has been run.
• The Sweave manual is now included as a vignette in the utils
package.
• Sweave() handles keep.source=TRUE much better: it could duplicate
some lines and omit comments. (Reported by John Maindonald and
others.)
C-LEVEL FACILITIES:
• Because they use a C99 interface which a C++ compiler is not
required to support, Rvprintf and REvprintf are only defined by
R_ext/Print.h in C++ code if the macro R_USE_C99_IN_CXX is
defined when it is included.
• pythag duplicated the C99 function hypot. It is no longer
provided, but is used as a substitute for hypot in the very
unlikely event that the latter is not available.
• R_inspect(obj) and R_inspect3(obj, deep, pvec) are (hidden)
C-level entry points to the internal inspect function and can be
used for C-level debugging (e.g., in conjunction with the p
command in gdb).
• Compiling R with --enable-strict-barrier now also enables
additional checking for use of unprotected objects. In
combination with gctorture() or gctorture2() and a C-level
debugger this can be useful for tracking down memory protection
issues.
UTILITIES:
• R CMD Rdiff is now implemented in R on Unix-alikes (as it has
been on Windows since R 2.12.0).
• R CMD build no longer does any cleaning in the supplied package
directory: all the cleaning is done in the copy.
It has a new option --install-args to pass arguments to R CMD
INSTALL for --build (but not when installing to rebuild
vignettes).
There is new option, --resave-data, to call
tools::resaveRdaFiles() on the data directory, to compress
tabular files (.tab, .csv etc) and to convert .R files to .rda
files. The default, --resave-data=gzip, is to do so in a way
compatible even with years-old versions of R, but better
compression is given by --resave-data=best, requiring R >=
2.10.0.
It now adds a datalist file for data directories of more than
1Mb.
Patterns in .Rbuildignore are now also matched against all
directory names (including those of empty directories).
There is a new option, --compact-vignettes, to try reducing the
size of PDF files in the inst/doc directory. Currently this
tries qpdf: other options may be used in future.
When re-building vignettes and a inst/doc/Makefile file is found,
make clean is run if the makefile has a clean: target.
After re-building vignettes the default clean-up operation will
remove any directories (and not just files) created during the
process: e.g. one package created a .R_cache directory.
Empty directories are now removed unless the option
--keep-empty-dirs is given (and a few packages do deliberately
include empty directories).
If there is a field BuildVignettes in the package DESCRIPTION
file with a false value, re-building the vignettes is skipped.
• R CMD check now also checks for filenames that are
case-insensitive matches to Windows' reserved file names with
extensions, such as nul.Rd, as these have caused problems on some
Windows systems.
It checks for inefficiently saved data/*.rda and data/*.RData
files, and reports on those large than 100Kb. A more complete
check (including of the type of compression, but potentially much
slower) can be switched on by setting environment variable
_R_CHECK_COMPACT_DATA2_ to TRUE.
The types of files in the data directory are now checked, as
packages are _still_ misusing it for non-R data files.
It now extracts and runs the R code for each vignette in a
separate directory and R process: this is done in the package's
declared encoding. Rather than call tools::checkVignettes(), it
calls tool::buildVignettes() to see if the vignettes can be
re-built as they would be by R CMD build. Option --use-valgrind
now applies only to these runs, and not when running code to
rebuild the vignettes. This version does a much better job of
suppressing output from successful vignette tests.
The 00check.log file is a more complete record of what is output
to stdout: in particular contains more details of the tests.
It now check all syntactically valid Rd usage entries, and warns
about assignments (unless these give the usage of replacement
functions).
.tar.xz compressed tarballs are now allowed, if tar supports them
(and setting environment variable TAR to internal ensures so on
all platforms).
• R CMD check now warns if it finds inst/doc/makefile, and R CMD
build renames such a file to inst/doc/Makefile.
INSTALLATION:
• Installing R no longer tries to find perl, and R CMD no longer
tries to substitute a full path for awk nor perl - this was a
legacy from the days when they were used by R itself. Because a
couple of packages do use awk, it is set as the make (rather than
environment) variable AWK.
• make check will now fail if there are differences from the
reference output when testing package examples and if environment
variable R_STRICT_PACKAGE_CHECK is set to a true value.
• The C99 double complex type is now required.
The C99 complex trigonometric functions (such as csin) are not
currently required (FreeBSD lacks most of them): substitutes are
used if they are missing.
• The C99 system call va_copy is now required.
• If environment variable R_LD_LIBRARY_PATH is set during
configuration (for example in config.site) it is used unchanged
in file etc/ldpaths rather than being appended to.
• configure looks for support for OpenMP and if found compiles R
with appropriate flags and also makes them available for use in
packages: see ‘Writing R Extensions’.
This is currently experimental, and is only used in R with a
single thread for colSums() and colMeans(). Expect it to be more
widely used in later versions of R.
This can be disabled by the --disable-openmp flag.
PACKAGE INSTALLATION:
• R CMD INSTALL --clean now removes copies of a src directory which
are created when multiple sub-architectures are in use.
(Following a comment from Berwin Turlach.)
• File R.css is now installed on a per-package basis (in the
package's html directory) rather than in each library tree, and
this is used for all the HTML pages in the package. This helps
when installing packages with static HTML pages for use on a
webserver. It will also allow future versions of R to use
different stylesheets for the packages they install.
• A top-level file .Rinstignore in the package sources can list (in
the same way as .Rbuildignore) files under inst that should not
be installed. (Why should there be any such files? Because all
the files needed to re-build vignettes need to be under inst/doc,
but they may not need to be installed.)
• R CMD INSTALL has a new option --compact-docs to compact any PDFs
under the inst/doc directory. Currently this uses qpdf, which
must be installed (see ‘Writing R Extensions’).
• There is a new option --lock which can be used to cancel the
effect of --no-lock or --pkglock earlier on the command line.
• Option --pkglock can now be used with more than one package, and
is now the default if only one package is specified.
• Argument lock of install.packages() can now be use for Mac binary
installs as well as for Windows ones. The value "pkglock" is now
accepted, as well as TRUE and FALSE (the default).
• There is a new option --no-clean-on-error for R CMD INSTALL to
retain a partially installed package for forensic analysis.
• Packages with names ending in . are not portable since Windows
does not work correctly with such directory names. This is now
warned about in R CMD check, and will not be allowed in R 2.14.x.
• The vignette indices are more comprehensive (in the style of
browseVignetttes()).
DEPRECATED & DEFUNCT:
• require(save = TRUE) is defunct, and use of the save argument is
deprecated.
• R CMD check --no-latex is defunct: use --no-manual instead.
• R CMD Sd2Rd is defunct.
• The gamma argument to hsv(), rainbow(), and rgb2hsv() is
deprecated and no longer has any effect.
• The previous options for R CMD build --binary (--auto-zip,
--use-zip-data and --no-docs) are deprecated (or defunct): use
the new option --install-args instead.
• When a character value is used for the EXPR argument in switch(),
only a single unnamed alternative value is now allowed.
• The wrapper utils::link.html.help() is no longer available.
• Zip-ing data sets in packages (and hence R CMD INSTALL options
--use-zip-data and --auto-zip, as well as the ZipData: yes field
in a DESCRIPTION file) is defunct.
Installed packages with zip-ed data sets can still be used, but a
warning that they should be re-installed will be given.
• The ‘experimental’ alternative specification of a name space via
.Export() etc is now defunct.
• The option --unsafe to R CMD INSTALL is deprecated: use the
identical option --no-lock instead.
• The entry point pythag in Rmath.h is deprecated in favour of the
C99 function hypot. A wrapper for hypot is provided for R 2.13.x
only.
• Direct access to the "source" attribute of functions is
deprecated; use deparse(fn, control="useSource") to access it,
and removeSource(fn) to remove it.
• R CMD build --binary is now formally deprecated: R CMD INSTALL
--build has long been the preferred alternative.
• Single-character package names are deprecated (and R is already
disallowed to avoid confusion in Depends: fields).
BUG FIXES:
• drop.terms and the [ method for class "terms" no longer add back
an intercept. (Reported by Niels Hansen.)
• aggregate preserves the class of a column (e.g. a date) under
some circumstances where it discarded the class previously.
• p.adjust() now always returns a vector result, as documented. In
previous versions it copied attributes (such as dimensions) from
the p argument: now it only copies names.
• On PDF and PostScript devices, a line width of zero was recorded
verbatim and this caused problems for some viewers (a very thin
line combined with a non-solid line dash pattern could also cause
a problem). On these devices, the line width is now limited at
0.01 and for very thin lines with complex dash patterns the
device may force the line dash pattern to be solid. (Reported by
Jari Oksanen.)
• The str() method for class "POSIXt" now gives sensible output for
0-length input.
• The one- and two-argument complex maths functions failed to warn
if NAs were generated (as their numeric analogues do).
• Added .requireCachedGenerics to the dont.mind list for library()
to avoid warnings about duplicates.
• $<-.data.frame messed with the class attribute, breaking any S4
subclass. The S4 data.frame class now has its own $<- method,
and turns dispatch on for this primitive.
• Map() did not look up a character argument f in the correct
frame, thanks to lazy evaluation. (PR#14495)
• file.copy() did not tilde-expand from and to when to was a
directory. (PR#14507)
• It was possible (but very rare) for the loading test in R CMD
INSTALL to crash a child R process and so leave around a lock
directory and a partially installed package. That test is now
done in a separate process.
• plot(<formula>, data=<matrix>,..) now works in more cases;
similarly for points(), lines() and text().
• edit.default() contained a manual dispatch for matrices (the
"matrix" class didn't really exist when it was written). This
caused an infinite recursion in the no-GUI case and has now been
removed.
• data.frame(check.rows = TRUE) sometimes worked when it should
have detected an error. (PR#14530)
• scan(sep= , strip.white=TRUE) sometimes stripped trailing spaces
from within quoted strings. (The real bug in PR#14522.)
• The rank-correlation methods for cor() and cov() with use =
"complete.obs" computed the ranks before removing missing values,
whereas the documentation implied incomplete cases were removed
first. (PR#14488)
They also failed for 1-row matrices.
• The perpendicular adjustment used in placing text and expressions
in the margins of plots was not scaled by par("mex"). (Part of
PR#14532.)
• Quartz Cocoa device now catches any Cocoa exceptions that occur
during the creation of the device window to prevent crashes. It
also imposes a limit of 144 ft^2 on the area used by a window to
catch user errors (unit misinterpretation) early.
• The browser (invoked by debug(), browser() or otherwise) would
display attributes such as "wholeSrcref" that were intended for
internal use only.
• R's internal filename completion now properly handles filenames
with spaces in them even when the readline library is used. This
resolves PR#14452 provided the internal filename completion is
used (e.g., by setting rc.settings(files = TRUE)).
• Inside uniroot(f, ...), -Inf function values are now replaced by
a maximally *negative* value.
• rowsum() could silently over/underflow on integer inputs
(reported by Bill Dunlap).
• as.matrix() did not handle "dist" objects with zero rows.
CHANGES IN R VERSION 2.12.2 patched:
NEW FEATURES:
• max() and min() work harder to ensure that NA has precedence over
NaN, so e.g. min(NaN, NA) is NA. (This was not previously
documented except for within a single numeric vector, where
compiler optimizations often defeated the code.)
BUG FIXES:
• A change to the C function R_tryEval had broken error messages in
S4 method selection; the error message is now printed.
• PDF output with a non-RGB color model used RGB for the line
stroke color. (PR#14511)
• stats4::BIC() assumed without checking that an object of class
"logLik" has an "nobs" attribute: glm() fits did not and so BIC()
failed for them.
• In some circumstances a one-sided mantelhaen.test() reported the
p-value for the wrong tail. (PR#14514)
• Passing the invalid value lty = NULL to axis() sent an invalid
value to the graphics device, and might cause the device to
segfault.
• Sweave() with concordance=TRUE could lead to invalid PDF files;
Sweave.sty has been updated to avoid this.
• Non-ASCII characters in the titles of help pages were not
rendered properly in some locales, and could cause errors or
warnings. • checkRd() gave a spurious error if the \href macro was used.
On a whim, I took the all time stats of my blog posts (more than 1000 posts) , and tried to plot their distribution.
Basically I copied and pasted all the data in a Google docs spreadsheet. and I created dummy codes (like URL1, URL2…. URL 500)
Next I downloaded the….
I wasnt in the mood for downloading and uploading stuff so I decided to use GGPLOT using Jeroen’s Application at http://www.stat.ucla.edu/~jeroen/
I used the mirror server that Dataspora provides as I have had latency issues with Jeroen’s website.
I got this error while trying to connect the Dataspora App to my Google spreadsheet
The page you have requested cannot be displayed. Another site was requesting access to your Google Account, but sent a malformed request. Please contact the site that you were trying to use when you received this message to inform them of the error. A detailed error message follows:
The site “http://dataspora.com” has not been registered.
Oh dear! Back to Jeroen’s /UCLA’s page.
http://rweb.stat.ucla.edu/ggplot2/
I get this warning but it still manages to log in
This website has not registered with Google to establish a secure connection for authorization requests. We recommend that you continue the process only if you trust the following destination:
http://rweb.stat.ucla.edu/R/googleLogin?domain=rweb.stat.ucla.edu
wow it works! thats cloud computing now so I wonder why Google and Amazon continue to ignore the rApache, and Jeroen’s cloud app . Surely their Google Fusion Tables can be always improved or tweaked. Not to mention the next gen version of R which will have its own server
Pretty cool screenshot (but click to see more)
I get the following pretty graph. Hadley Wickham would be ashamed of me by now.
What went wrong- well one page has 36000 views . Scale is the key to graphical coherence . So I redo- delete home page in Google spreadsheet ,reimport replot. ( I didnt know how to modify data in the cloud app, maybe we need a cloud PlyR) I redo it again as I have a big outlier-The top 10 Statistical GUI article which ironically has only 5 GUIs in that article but hush dont tell to high quality search engine)
So again Belatedly I discover something called layer in ggplot.
Base Graphics engine has really spoilt me to write short functions for plots. 
I give up. I rather prefer hist() I go to my favorite GUI Rattle, but it has some dating issues with the dll of GTK+
So I go to John Fox’s simple GUI. R Commander- is the best GUI if you use Occam’s Razor, and I am using Occam’s Chainsaw now.
I get the analysis I want in 12 secs
Summary- GGPLot is more complicated than base graphics engine.
Deducer GUI is not as simple too
R Commander is the best GUI because it retains simplicity
Ignore long tail of internet only at your peril
Almost 2/3 rds of my daily traffic of 400+ comes from old archived content That is why Search Engine Optimization and Alerts for Keywords are CRITICAL for any poor soul trying to write on a blog (which has no journal like prestige nor rewards)
If you make life easier for the search engine, it being a fair chap, rewards you well
Existing web traffic estimates like Comscore and Google Trends ignore this long tail
Comments are welcome (Data is pasted below of 500 rows X 2 columns if you can come up with a better analysis)
Since SAS has ignored web analytics and Google Analytics is hmm hmm, this could be an area of opportunity for R developers as well to create a web analytics package.
R has almost 2923 available packages
This makes the task of searching among these packages and comparing functions for the same analytical task across different packages a bit tedious and prone to manual searching (of reading multiple Pdfs of help /vignette of packages) or sending an email to the R help list.
However using R Views is a slightly better way of managing all your analytical requirements for software rather than the large number of packages (see Graphics view below).
CRAN Task Views allow you to browse packages by topic and provide tools to automatically install all packages for special areas of interest. Currently, 28 views are available. http://cran.r-project.org/web/views/
Bayesian Bayesian Inference ChemPhys Chemometrics and Computational Physics ClinicalTrials Clinical Trial Design, Monitoring, and Analysis Cluster Cluster Analysis & Finite Mixture Models Distributions Probability Distributions Econometrics Computational Econometrics Environmetrics Analysis of Ecological and Environmental Data ExperimentalDesign Design of Experiments (DoE) & Analysis of Experimental Data Finance Empirical Finance Genetics Statistical Genetics Graphics Graphic Displays & Dynamic Graphics & Graphic Devices & Visualization gR gRaphical Models in R HighPerformanceComputing High-Performance and Parallel Computing with R MachineLearning Machine Learning & Statistical Learning MedicalImaging Medical Image Analysis Multivariate Multivariate Statistics NaturalLanguageProcessing Natural Language Processing OfficialStatistics Official Statistics & Survey Methodology Optimization Optimization and Mathematical Programming Pharmacokinetics Analysis of Pharmacokinetic Data Phylogenetics Phylogenetics, Especially Comparative Methods Psychometrics Psychometric Models and Methods ReproducibleResearch Reproducible Research Robust Robust Statistical Methods SocialSciences Statistics for the Social Sciences Spatial Analysis of Spatial Data Survival Survival Analysis TimeSeries Time Series Analysis To automatically install these views, the ctv package needs to be installed, e.g., via
install.packages("ctv") library("ctv")Created by Pretty R at inside-R.org
and then the views can be installed via install.views or update.views (which first assesses which of the packages are already installed and up-to-date), e.g.,install.views("Econometrics") update.views("Econometrics") Created by Pretty R at inside-R.org
| Maintainer: | Nicholas Lewin-Koh |
| Contact: | nikko at hailmail.net |
| Version: | 2009-10-28 |
R is rich with facilities for creating and developing interesting graphics. Base R contains functionality for many plot types including coplots, mosaic plots, biplots, and the list goes on. There are devices such as postscript, png, jpeg and pdf for outputting graphics as well as device drivers for all platforms running R. lattice and grid are supplied with R’s recommended packages and are included in every binary distribution. lattice is an R implementation of William Cleveland’s trellis graphics, while grid defines a much more flexible graphics environment than the base R graphics.
R’s base graphics are implemented in the same way as in the S3 system developed by Becker, Chambers, and Wilks. There is a static device, which is treated as a static canvas and objects are drawn on the device through R plotting commands. The device has a set of global parameters such as margins and layouts which can be manipulated by the user using par() commands. The R graphics engine does not maintain a user visible graphics list, and there is no system of double buffering, so objects cannot be easily edited without redrawing a whole plot. This situation may change in R 2.7.x, where developers are working on double buffering for R devices. Even so, the base R graphics can produce many plots with extremely fine graphics in many specialized instances.
One can quickly run into trouble with R’s base graphic system if one wants to design complex layouts where scaling is maintained properly on resizing, nested graphs are desired or more interactivity is needed. grid was designed by Paul Murrell to overcome some of these limitations and as a result packages like lattice, ggplot2, vcd or hexbin (on Bioconductor ) use grid for the underlying primitives. When using plots designed with grid one needs to keep in mind that grid is based on a system of viewports and graphic objects. To add objects one needs to use grid commands, e.g., grid.polygon() rather than polygon(). Also grid maintains a stack of viewports from the device and one needs to make sure the desired viewport is at the top of the stack. There is a great deal of explanatory documentation included with grid as vignettes.
The graphics packages in R can be organized roughly into the following topics, which range from the more user oriented at the top to the more developer oriented at the bottom. The categories are not mutually exclusive but are for the convenience of presentation:
DECISION STATS 