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Amazon Ec2 goes Red Hat

message from Amazing Amazon’s cloud team- this will also help for #rstats users given that revolution Analytics full versions on RHEL.


on-demand instances of Amazon EC2 running Red Hat Enterprise Linux (RHEL) for as little as $0.145 per instance hour. The offering combines the cost-effectiveness, scalability and flexibility of running in Amazon EC2 with the proven reliability of Red Hat Enterprise Linux.

Highlights of the offering include:

  • Support is included through subscription to AWS Premium Support with back-line support by Red Hat
  • Ongoing maintenance, including security patches and bug fixes, via update repositories available in all Amazon EC2 regions
  • Amazon EC2 running RHEL currently supports RHEL 5.5, RHEL 5.6, RHEL 6.0 and RHEL 6.1 in both 32 bit and 64 bit formats, and is available in all Regions.
  • Customers who already own Red Hat licenses will continue to be able to use those licenses at no additional charge.
  • Like all services offered by AWS, Amazon EC2 running Red Hat Enterprise Linux offers a low-cost, pay-as-you-go model with no long-term commitments and no minimum fees.

For more information, please visit the Amazon EC2 Red Hat Enterprise Linux page.

which is

Amazon EC2 Running Red Hat Enterprise Linux

Amazon EC2 running Red Hat Enterprise Linux provides a dependable platform to deploy a broad range of applications. By running RHEL on EC2, you can leverage the cost effectiveness, scalability and flexibility of Amazon EC2, the proven reliability of Red Hat Enterprise Linux, and AWS premium support with back-line support from Red Hat.. Red Hat Enterprise Linux on EC2 is available in versions 5.5, 5.6, 6.0, and 6.1, both in 32-bit and 64-bit architectures.

Amazon EC2 running Red Hat Enterprise Linux provides seamless integration with existing Amazon EC2 features including Amazon Elastic Block Store (EBS), Amazon CloudWatch, Elastic-Load Balancing, and Elastic IPs. Red Hat Enterprise Linux instances are available in multiple Availability Zones in all Regions.

Sign Up


Pay only for what you use with no long-term commitments and no minimum fee.

On-Demand Instances

On-Demand Instances let you pay for compute capacity by the hour with no long-term commitments.

Region:US – N. VirginiaUS – N. CaliforniaEU – IrelandAPAC – SingaporeAPAC – Tokyo
Standard Instances Red Hat Enterprise Linux
Small (Default) $0.145 per hour
Large $0.40 per hour
Extra Large $0.74 per hour
Micro Instances Red Hat Enterprise Linux
Micro $0.08 per hour
High-Memory Instances Red Hat Enterprise Linux
Extra Large $0.56 per hour
Double Extra Large $1.06 per hour
Quadruple Extra Large $2.10 per hour
High-CPU Instances Red Hat Enterprise Linux
Medium $0.23 per hour
Extra Large $0.78 per hour
Cluster Compute Instances Red Hat Enterprise Linux
Quadruple Extra Large $1.70 per hour
Cluster GPU Instances Red Hat Enterprise Linux
Quadruple Extra Large $2.20 per hour

Pricing is per instance-hour consumed for each instance type. Partial instance-hours consumed are billed as full hours.

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Available Instance Types

Standard Instances

Instances of this family are well suited for most applications.

Small Instance – default*

1.7 GB memory
1 EC2 Compute Unit (1 virtual core with 1 EC2 Compute Unit)
160 GB instance storage
32-bit platform
I/O Performance: Moderate
API name: m1.small

Large Instance

7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large

Extra Large Instance

15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge

Micro Instances

Instances of this family provide a small amount of consistent CPU resources and allow you to burst CPU capacity when additional cycles are available. They are well suited for lower throughput applications and web sites that consume significant compute cycles periodically.

Micro Instance

613 MB memory
Up to 2 EC2 Compute Units (for short periodic bursts)
EBS storage only
32-bit or 64-bit platform
I/O Performance: Low
API name: t1.micro

High-Memory Instances

Instances of this family offer large memory sizes for high throughput applications, including database and memory caching applications.

High-Memory Extra Large Instance

17.1 GB of memory
6.5 EC2 Compute Units (2 virtual cores with 3.25 EC2 Compute Units each)
420 GB of instance storage
64-bit platform
I/O Performance: Moderate
API name: m2.xlarge

High-Memory Double Extra Large Instance

34.2 GB of memory
13 EC2 Compute Units (4 virtual cores with 3.25 EC2 Compute Units each)
850 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.2xlarge

High-Memory Quadruple Extra Large Instance

68.4 GB of memory
26 EC2 Compute Units (8 virtual cores with 3.25 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.4xlarge

High-CPU Instances

Instances of this family have proportionally more CPU resources than memory (RAM) and are well suited for compute-intensive applications.

High-CPU Medium Instance

1.7 GB of memory
5 EC2 Compute Units (2 virtual cores with 2.5 EC2 Compute Units each)
350 GB of instance storage
32-bit platform
I/O Performance: Moderate
API name: c1.medium

High-CPU Extra Large Instance

7 GB of memory
20 EC2 Compute Units (8 virtual cores with 2.5 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: c1.xlarge

Cluster Compute Instances

Instances of this family provide proportionally high CPU resources with increased network performance and are well suited for High Performance Compute (HPC) applications and other demanding network-bound applications. Learn more about use of this instance type for HPC applications.

Cluster Compute Quadruple Extra Large Instance

23 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cc1.4xlarge

Cluster GPU Instances

Instances of this family provide general-purpose graphics processing units (GPUs) with proportionally high CPU and increased network performance for applications benefitting from highly parallelized processing, including HPC, rendering and media processing applications. While Cluster Compute Instances provide the ability to create clusters of instances connected by a low latency, high throughput network, Cluster GPU Instances provide an additional option for applications that can benefit from the efficiency gains of the parallel computing power of GPUs over what can be achieved with traditional processors. Learn more about use of this instance type for HPC applications.

Cluster GPU Quadruple Extra Large Instance

22 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cg1.4xlarge


Getting Started

To get started using Red Hat Enterprise Linux on Amazon EC2, perform the following steps:

  • Open and log into the AWS Management Console
  • Click on Launch Instance from the EC2 Dashboard
  • Select the Red Hat Enterprise Linux AMI from the QuickStart tab
  • Specify additional details of your instance and click Launch
  • Additional details can be found on each AMI’s Catalog Entry page

The AWS Management Console is an easy tool to start and manage your instances. If you are looking for more details on launching an instance, a quick video tutorial on how to use Amazon EC2 with the AWS Management Console can be found here .
A full list of Red Hat Enterprise Linux AMIs can be found in the AWS AMI Catalog.

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All customers running Red Hat Enterprise Linux on EC2 will receive access to repository updates from Red Hat. Moreover, AWS Premium support customers can contact AWS to get access to a support structure from both Amazon and Red Hat.

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About Red Hat

Red Hat, the world’s leading open source solutions provider, is headquartered in Raleigh, NC with over 50 satellite offices spanning the globe. Red Hat provides high-quality, low-cost technology with its operating system platform, Red Hat Enterprise Linux, together with applications, management and Services Oriented Architecture (SOA) solutions, including the JBoss Enterprise Middleware Suite. Red Hat also offers support, training and consulting services to its customers worldwide.


also from Revolution Analytics- in case you want to #rstats in the cloud and thus kill all that talk of RAM dependency, slow R than other softwares (just increase the RAM above in the instances to keep it simple)

,or Revolution not being open enough



Revolution Analytics uses an Open-Core Licensing model. We provide open- source R bundled with proprietary modules from Revolution Analytics that provide additional functionality for our users. Open-source R is distributed under the GNU Public License (version 2), and we make our software available under a commercial license.

Revolution Analytics respects the importance of open source licenses and has contributed code to the open source R project and will continue to do so. We have carefully reviewed our compliance with GPLv2 and have worked with Mark Radcliffe of DLA Piper, the outside General Legal Counsel of the Open Source Initiative, to ensure that we fully comply with the obligations of the GPLv2.

For our Revolution R distribution, we may make some minor modifications to the R sources (the ChangeLog file lists all changes made). You can download these modified sources of open-source R under the terms of the GPLv2, using either the links below or those in the email sent to you when you download a specific version of Revolution R.

Download GPL Sources

Product Version Platform Modified R Sources
Revolution R Community 3.2 Windows R 2.10.1
Revolution R Community 3.2 MacOS R 2.10.1
Revolution R Enterprise 3.1.1 RHEL R 2.9.2
Revolution R Enterprise 4.0 Windows R 2.11.1
Revolution R Enterprise 4.0.1 RHEL R 2.11.1
Revolution R Enterprise 4.1.0 Windows R 2.11.1
Revolution R Enterprise 4.2 Windows R 2.11.1
Revolution R Enterprise 4.2 RHEL R 2.11.1
Revolution R Enterprise 4.3 Windows & RHEL R 2.12.2




Revolution releases R Windows for Academics for free

Logo for R

Image via Wikipedia

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.


Changes in R software

The newest version of R is now available for download. R 2.13 is ready !!




Windows-specific changes to R





  • Windows 2000 is no longer supported. (It went end-of-life in July 2010.)






  • 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.) 


  • Support for repository type win64.binary (used for 64-bit Windows binaries for R 2.11.x only) has been removed. 


  • The installers no longer put an ‘Uninstall’ item on the start menu (to conform to current Microsoft UI guidelines). 


  • Running R always sets the environment variable R_ARCH (as it does on a Unix-alike from the shell-script front-end). 


  • The defaults for 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). 


  • If 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. 


  • The versions of 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’. 


  • A few more file operations will now work with >2GB files. 


  • The environment variable R_HOME in an R session now uses slash as the path separator (as it always has when set by Rcmd.exe). 


  • Rgui has a new menu item for the PDF ‘Sweave User Manual’.






  • zip.unpack() is deprecated: use unzip().




  • There is support for libjpeg-turbo via setting JPEGDIR to that value in ‘MkRules.local’. 

    Support for jpeg-6b has been removed.


  • The sources now work with libpng-1.5.1, jpegsrc.v8c (which are used in the CRAN builds) and tiff-4.0.0beta6 (CRAN builds use 3.9.1). It is possible that they no longer work with older versions than libpng-1.4.5.






  • Workaround for the incorrect values given by Windows’ casinh function on the branch cuts.
  • Bug fixes for drawing raster objects on 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.
  • Printing extremely long string values could overflow the stack and cause the GUI to crash. (PR#14543)

Tonnes of 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.


    • 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

    • system.file() gains a mustWork argument (suggestion of Bill

    • 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

      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

    • 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

    • 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

    • 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

    • 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

    • 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

    • 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

    • file.copy() now (by default) copies read/write/execute
      permissions on files, moderated by the current setting of

    • 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

    • as.raster() no longer fails for vectors or matrices containing

    • 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

    • unlink() now does tilde-expansion (like most other file

    • 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

    • 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

    • 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

    • 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

    • 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,
      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


    • 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

    • Sweave() handles keep.source=TRUE much better: it could duplicate
      some lines and omit comments. (Reported by John Maindonald and


    • 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


    • 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

      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 >=

      It now adds a datalist file for data directories of more than

      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

      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

      .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.


    • 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.


    • 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


    • require(save = TRUE) is defunct, and use of the save argument is

    • 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

    • 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).


    • 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

    • 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

    • 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:


    • 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.)


    • 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

    • 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.



Why search optimization can make you like Rebecca Black

Felicia Day, actress and web content producer.

Image via Wikipedia

A highly optimized blog post or web content can get you a lot of attention just like Rebecca Black’s video (provided it passes through the new quality metrics \change*/ in the Search Engine)

But if the underlying content is weak, or based on a shoddy understanding of the content-it can drive lots of horrid comments as well as ensuring that bad word of mouth is spread about the content or you/despite your hard work.

An example of this is copy and paste journalism especially in technology circles, where even a bigger Page Ranked website /blog can get away with scraping or stealing content from a lower page ranked website (or many websites)  after adding a cursory “expert comment”. This is also true when someone who is basically a corporate communication specialist (or PR -public relations) person is given a techinical text and encourage to write about it without completely understanding it.

A mild technical defect in the search engine algorithm is that it does not seem to pay attention to when the content was published, so the copying website or blog actually can get by as fresher content even if it is practically has 90% of the same words). The second flaw is over punishment or manual punishment of excessive linking – this can encourage search optimization minded people to hoard links or discourage trackbacks.

A free internet is one which promotes free sharing of content and does not encourage stealing or un-authorized scraping or content copying. Unfortunately current search engine optimization can encourage scraping and content copying without paying too much attention to origin of the words.

In addition the analytical rigor by which search algorithms search your inboxes (as in search all emails for a keyword) or media rich sites (like Youtube) are quite on a different level of quality altogether. The chances of garbage results are much more while searching for media content and/or emails.

Is Random Poetry Click Fraud


Image via Wikipedia

Is poetry when randomized

Tweaked, meta tagged , search engine optimized

Violative of unseen terms and conditional clauses

Is random poetry or aggregated prose farmed for click fraud uses




I dont know, you tell me, says the blog boy,

Tapping away at the keyboard like a shiny new toy,

Geeks unfortunately too often are men too many,

Forgive the generalization, but the tech world is yet to be equalized.


If a New York Hot Dog  is a slice of heaven at four bucks a piece

Then why is prose and poetry at five bucks an hour considered waste

Ah I see, you have grown old and cynical,

Of the numerous stupid internet capers and cyber ways


The clicking finger clicks on

swiftly but mostly delightfully virally moves on

While people collect its trails and

ponder its aggregated merry ways


All people are equal but all links are not,

Thus overturning two centuries of psychology had you been better taught,

But you chose to drop out of school, and create that search engine so big

It is now a fraud catchers head ache that millions try to search engine optimize and rig


Once again, people are different, in so many ways so prettier

Links are the same hyper linked code number five or earlier

People think like artificial artificial (thus natural) neural nets

Biochemically enhanced Harmonically possessed.


rather than  analyze forensically and quite creepily

where people have been

Gentic Algorithms need some chaos

To see what till now hasnt been seen.


Again this was a random poem,

inspired by a random link that someone clicked

To get here, on a carbon burning cyber machine,

Having digested poem, moves on, unheard , unseen.

(Inspired by the Hyper Link at http://goo.gl/a8ijW )


Towards better quantitative marketing

Cycle of Research and Development, from "...

Image via Wikipedia

The term quantitative refers to a type of information based in quantities or else quantifiable data (objective properties) —as opposed to qualitative information which deals with apparent qualities (subjective properties)


Fear, uncertainty, and doubt (FUD) is a tactic of rhetoric and fallacy used in sales, marketing, public relations,[1][2] politics and propaganda. FUD is generally a strategic attempt to influence public perception by disseminating negative and dubious/false information designed to undermine the credibility of their beliefs.



Top 5 FUD Tactics in Software and what you can say to end user to retain credibility

1) That software lacks reliable support- our support team has won top prizes in Customer Appreciation for past several years.

  • Our software release history-
  • graph of bugs filed-
  • turn around time box plot for customer service issues
  • quantitatively define reliability

2) We give the best value to customers. Customer Big A got huge huge % savings thanks to our software.

  • Pricing- Transparent – and fixed. For volume discounts mention slabs.
  • Cost to Customer- Include time and cost estimates for training and installation
  • Graphs of average ROIC (return on capital invested) on TCO (total cost of ownership)  not half a dozen outlier case studies. Mention Expected % return

3) We have invested a lot of money in our Research and Development. We continue to spend a lotto of money on R &D

  • Average Salary of R and D employee versus Average Tenure (Linkedin gives the second metric quite easily)
  • Mention Tax benefits and Accounting treatment of R&D expenses
  • Give a breakdown- how much went to research and how much went to legacy application support
  • Mention open source projects openly
  • Mention community source projects separately

4) Software B got sued. Intellectual property rights (sniff)

  • Mention pending cases with your legal team
  • Mention anti trust concerns for potential acquisitions
  • Mention links to your patent portfolio (or even to US PTO with query ?=your corporate name )

5) We have a 99.8% renewal rate.

  • Mention vendor lock in concerns and flexibility
  • Mention What-If scenarios if there are delays in software implementation
  • Mention methodology in calculating return on investment.







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