The impact of currency fluctuations on outsourcing businesses globally.
If you have a current offshore team in a different country/currency zone then you may find that the significant cost savings from outsourcing have vanished due to currency fluctuations that occur for reasons like earthquakes, war or oil- something which is outside the core competency of your business corporation. As off shoring companies incur cost in local currencies but gain revenue in American Dollars and Euro (mostly), they pass on these fluctuating costs to their customers but rarely pass along discounts on existing contracts. Sometimes the offshoring contract actually gains from currency fluctuations.The Indian rupee has fluctuated from 43.62 Rupees per USD (04-01-2005) to 48.58 (12-31-2008) to the current value of 44.65.This makes for a volatility component of almost 10 percentage points to the revenue and profit margins of an off shoring vendor. Inflation in India has been growing at 8.5 % and the annual increase in salaries has been around 10-15 % for the past few years. Offshoring vendors have been known to cut back on quality in recruitment when costs have risen historically, and the current attrition rate in Indian ITES is almost 17%.
This raises important questions for companies going for global bids for the offshoring contracts. Should macroeconomic indicators like currency fluctuations, wage-inflation be part of the request for proposal process (RFP). Would vendors be comfortable in disclosing the ratio of salary costs to billing revenue. Should dips in service quality be penalized by customer. Most importantly, while going in for a multi year contract, the projection of fore-casted savings may vary greatly due to extraneous factors.
Here is an interview with Anne Milley, a notable thought leader in the world of analytics. Anne is now Senior Director, Analytical Strategy in Product Marketing for JMP , the leading data visualization software from the SAS Institute.
Ajay-What do you think are the top 5 unique selling points of JMP compared to other statistical software in its category?
Anne-
JMP combines incredible analytic depth and breadth with interactive data visualization, creating a unique environment optimized for discovery and data-driven innovation.
With an extensible framework using JSL (JMP Scripting Language), and integration with SAS, R, and Excel, JMP becomes your analytic hub.
JMP is accessible to all kinds of users. A novice analyst can dig into an interactive report delivered by a custom JMP application. An engineer looking at his own data can use built-in JMP capabilities to discover patterns, and a developer can write code to extend JMP for herself or others.
State-of-the-art DOE capabilities make it easy for anyone to design and analyze efficient experiments to determine which adjustments will yield the greatest gains in quality or process improvement – before costly changes are made.
Not to mention, JMP products are exceptionally well designed and easy to use. See for yourself and check out the free trial at www.jmp.com.
Ajay- What are the challenges and opportunities of expanding JMP’s market share? Do you see JMP expanding its conferences globally to engage global audiences?
Anne-
We realized solid global growth in 2010. The release of JMP Pro and JMP Clinical last year along with continuing enhancements to the rest of the JMP family of products (JMP and JMP Genomics) should position us well for another good year.
With the growing interest in analytics as a means to sustained value creation, we have the opportunity to help people along their analytic journey – to get started, take the next step, or adopt new paradigms speeding their time to value. The challenge is doing that as fast as we would like.
We are hiring internationally to offer even more events, training and academic programs globally.
Ajay- What are the current and proposed educational and global academic initiatives of JMP? How can we see more JMP in universities across the world (say India- China etc)?
Anne-
We view colleges and universities both as critical incubators of future JMP users and as places where attitudes about data analysis and statistics are formed. We believe that a positive experience in learning statistics makes a person more likely to eventually want and need a product like JMP.
For most students – and particularly for those in applied disciplines of business, engineering and the sciences – the ability to make a statistics course relevant to their primary area of study fosters a positive experience. Fortunately, there is a trend in statistical education toward a more applied, data-driven approach, and JMP provides a very natural environment for both students and researchers.
Its user-friendly navigation, emphasis on data visualization and easy access to the analytics behind the graphics make JMP a compelling alternative to some of our more traditional competitors.
We’ve seen strong growth in the education markets in the last few years, and JMP is now used in nearly half of the top 200 universities in the US.
Internationally, we are at an earlier stage of market development, but we are currently working with both JMP and SAS country offices and their local academic programs to promote JMP. For example, we are working with members of the JMP China office and faculty at several universities in China to support the use of JMP in the development of a master’s curriculum in Applied Statistics there, touched on in this AMSTAT News article.
Ajay- What future trends do you see for 2011 in this market (say top 5)?
Anne-
Growing complexity of data (text, image, audio…) drives the need for more and better visualization and analysis capabilities to make sense of it all.
More “chief analytics officers” are making better use of analytic talent – people are the most important ingredient for success!
JMP has been on the vanguard of 64-bit development, and users are now catching up with us as 64-bit machines become more common.
Users should demand easy-to-use, exploratory and predictive modeling tools as well as robust tools to experiment and learn to help them make the best decisions on an ongoing basis.
All these factors and more fuel the need for the integration of flexible, extensible tools with popular analytic platforms.
Ajay-You enjoy organic gardening as a hobby. How do you think hobbies and unwind time help people be better professionals?
Anne-
I am lucky to work with so many people who view their work as a hobby. They have other interests too, though, some of which are work-related (statistics is relevant everywhere!). Organic gardening helps me put things in perspective and be present in the moment. More than work defines who you are. You can be passionate about your work as well as passionate about other things. I think it’s important to spend some leisure time in ways that bring you joy and contribute to your overall wellbeing and outlook.
Btw, nice interviews over the past several months—I hadn’t kept up, but will check it out more often!
Anne Milley is Senior Director of Analytics Strategy at JMP Product Marketing at SAS. Her ties to SAS began with bank failure prediction at Federal Home Loan Bank Dallas and continued at 7-Eleven Inc. She has authored papers and served on committees for F2006, KDD, SIAM, A2010 and several years of SAS’ annual data mining conference. Milley is a contributing faculty member for the International Institute of Analytics. anne.milley@jmp.com
This promotional offer enables you to try a limited amount of the Windows Azure platform at no charge. The subscription includes a base level of monthly compute hours, storage, data transfers, a SQL Azure database, Access Control transactions and Service Bus connections at no charge. Please note that any usage over this introductory base level will be charged at standard rates.
Included each month at no charge:
Windows Azure
25 hours of a small compute instance
500 MB of storage
10,000 storage transactions
SQL Azure
1GB Web Edition database (available for first 3 months only)
Windows Azure platform AppFabric
100,000 Access Control transactions
2 Service Bus connections
Data Transfers (per region)
500 MB in
500 MB out
Any monthly usage in excess of the above amounts will be charged at the standard rates. This introductory special will end on March 31, 2011 and all usage will then be charged at the standard rates.
As part of AWS’s Free Usage Tier, new AWS customers can get started with Amazon EC2 for free. Upon sign-up, new AWScustomers receive the following EC2 services each month for one year:
750 hours of EC2 running Linux/Unix Micro instance usage
750 hours of Elastic Load Balancing plus 15 GB data processing
10 GB of Amazon Elastic Block Storage (EBS) plus 1 million IOs, 1 GB snapshot storage, 10,000 snapshot Get Requests and 1,000 snapshot Put Requests
15 GB of bandwidth in and 15 GB of bandwidth out aggregated across all AWS services
Paid Instances-
Standard On-Demand Instances
Linux/UNIX Usage
Windows Usage
Small (Default)
$0.085 per hour
$0.12 per hour
Large
$0.34 per hour
$0.48 per hour
Extra Large
$0.68 per hour
$0.96 per hour
Micro On-Demand Instances
Micro
$0.02 per hour
$0.03 per hour
High-Memory On-Demand Instances
Extra Large
$0.50 per hour
$0.62 per hour
Double Extra Large
$1.00 per hour
$1.24 per hour
Quadruple Extra Large
$2.00 per hour
$2.48 per hour
High-CPU On-Demand Instances
Medium
$0.17 per hour
$0.29 per hour
Extra Large
$0.68 per hour
$1.16 per hour
Cluster Compute Instances
Quadruple Extra Large
$1.60 per hour
N/A*
Cluster GPU Instances
Quadruple Extra Large
$2.10 per hour
N/A*
* Windows is not currently available for Cluster Compute or Cluster GPU Instances.
NOTE- Amazon Instance definitions differ slightly from Azure definitions
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 moreabout 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
versus-
Windows Azure compute instances come in five unique sizes to enable complex applications and workloads.
Compute Instance Size
CPU
Memory
Instance Storage
I/O Performance
Extra Small
1 GHz
768 MB
20 GB*
Low
Small
1.6 GHz
1.75 GB
225 GB
Moderate
Medium
2 x 1.6 GHz
3.5 GB
490 GB
High
Large
4 x 1.6 GHz
7 GB
1,000 GB
High
Extra large
8 x 1.6 GHz
14 GB
2,040 GB
High
*There is a limitation on the Virtual Hard Drive (VHD) size if you are deploying a Virtual Machine role on an extra small instance. The VHD can only be up to 15 GB.
My annual traffic to this blog was almost 99,000 . Add in additional views on networking sites plus the 400 plus RSS readers- so I can say traffic was 1,20,000 for 2010. Nice. Thanks for reading and hope it was worth your time. (this is a long post and will take almost 440 secs to read but the summary is just given)
My intent is either to inform you, give something useful or atleast something interesting.
see below-
Jan
Feb
Mar
Apr
May
Jun
2010
6,311
4,701
4,922
5,463
6,493
4,271
Jul
Aug
Sep
Oct
Nov
Dec
Total
5,041
5,403
17,913
16,430
11,723
10,096
98,767
Sandro Saita from http://www.dataminingblog.com/ just named me for an award on his blog (but my surname is ohRi , Sandro left me without an R- What would I be without R :)) ).
Aw! I am touched. Google for “Data Mining Blog” and Sandro is the best that it is in data mining writing.
”
DMR People Award 2010
There are a lot of active people in the field of data mining. You can discuss with them on forums. You can read their blogs. You can also meet them in events such as PAW or KDD. Among the people I follow on a regular basis, I have elected:
Ajay Ori
He has been very active in 2010, especially on his blog . Good work Ajay and continue sharing your experience with us!”
What did I write in 2010- stuff.
What did you read on this blog- well thats the top posts list.
well I guess I owe Tal G for almost 9000 views ( incidentally I withdrew posting my blog from R- Bloggers and Analyticbridge blogs – due to SEO keyword reasons and some spam I was getting see (below))
Still reading this post- gosh let me sell you some advertising. It is only $100 a month (yes its a recession)
Advertisers are treated on First in -Last out (FILO)
I have been told I am obsessed with SEO , but I dont care much for search engines apart from Google, and yes SEO is an interesting science (they should really re name it GEO or Google Engine Optimization)
Apparently Hadley Wickham and Donald Farmer are big keywords for me so I should be more respectful I guess.
Search Terms for 365 days ending 2010-12-31 (Summarized)
2009-12-31 to Today
Search
Views
libre office
925
facebook analytics
798
test drive a chrome notebook
467
test drive a chrome notebook.
215
r gui
203
data mining
163
wps sas lawsuit
158
wordle.net
133
wps sas
123
google maps jet ski
123
test drive chrome notebook
96
sas wps
89
sas wps lawsuit
85
chrome notebook test drive
83
decision stats
83
best statistics software
74
hadley wickham
72
google maps jetski
72
libreoffice
70
doug savage
65
hive tutorial
58
funny india
56
spss certification
52
donald farmer microsoft
51
best statistical software
49
What about outgoing links? Apparently I need to find a way to ask Google to pay me for the free advertising I gave their chrome notebook launch. But since their search engine and browser is free to me, guess we are even steven.
Clicks for 365 days ending 2010-12-31 (Summarized)
Tableau was named by Software Magazine as the fastest growing software company in the $10 million to $30 million range in the world, and the second fastest growing software company worldwide overall. The ranking stems from the publication’s 28th annual Software 500 ranking of the world’s largest software service providers.
“We’re growing fast because the market is starving for easy-to-use products that deliver rapid-fire business intelligence to everyone. Our customers want ways to unlock their databases and produce engaging reports and dashboards,” said Christian Chabot CEO and co-founder of Tableau.
Put together an Academy-Award winning professor from the nation’s most prestigious university, a savvy business leader with a passion for data, and a brilliant computer scientist. Add in one of the most challenging problems in software – making databases and spreadsheets understandable to ordinary people. You have just recreated the fundamental ingredients for Tableau.
The catalyst? A Department of Defense (DOD) project aimed at increasing people’s ability to analyze information and brought to famed Stanford professor, Pat Hanrahan. A founding member of Pixar and later its chief architect for RenderMan, Pat invented the technology that changed the world of animated film. If you know Buzz and Woody of “Toy Story”, you have Pat to thank.
Under Pat’s leadership, a team of Stanford Ph.D.s got together just down the hall from the Google folks. Pat and Chris Stolte, the brilliant computer scientist, realized that data visualization could produce large gains in people’s ability to understand information. Rather than analyzing data in text form and then creating visualizations of those findings, Pat and Chris invented a technology called VizQL™ by which visualization is part of the journey and not just the destination. Fast analytics and visualization for everyone was born.
While satisfying the DOD project, Pat and Chris met Christian Chabot, a former data analyst who turned into Jello when he saw what had been invented. The three formed a company and spun out of Stanford like so many before them (Yahoo, Google, VMWare, SUN). With Christian on board as CEO, Tableau rapidly hit one success after another: its first customer (now Tableau’s VP, Operations, Tom Walker), an OEM deal with Hyperion (now Oracle), funding from New Enterprise Associates, a PC Magazine award for “Product of the Year” just one year after launch, and now over 50,000 people in 50+ countries benefiting from the breakthrough.
and now a demo I ran on the Kaggle contest data (it is a csv dataset with 95000 rows)
I found Tableau works extremely good at pivoting data and visualizing it -almost like Excel on Steroids. Download the free version here ( I dont know about an academic program (see links below) but software is not expensive at all)
The Professional Edition is a visual analysis and reporting solution for data stored in MS SQL Server, MS Analysis Services, Oracle, IBM DB2, Netezza, Hyperion Essbase, Teradata, Vertica, MySQL, PostgreSQL, Firebird, Excel, MS Access or Text Files. Available via download.
Tableau Server enables users of Tableau Desktop Professional to publish workbooks and visualizations to a server where users with web browsers can access and interact with the results. Available via download.
* Price is per Named User and includes one year of maintenance (upgrades and support). Products are made available as a download immediately after purchase. You may revisit the download site at any time during your current maintenance period to access the latest releases.
I am currently playing/ trying out RApache- one more excellent R product from Vanderbilt’s excellent Dept of Biostatistics and it’s prodigious coder Jeff Horner.
I really liked the virtual machine idea- you can download a virtual image of Rapache and play with it- .vmx is easy to create and great to share-
Basically using R Apache (with an EC2 on backend) can help you create customized dashboards, BI apps, etc all using R’s graphical and statistical capabilities.
Rapache embeds the R interpreter inside the Apache 2 web server. By doing this, Rapache realizes the full potential of R and its facilities over the web. R programmers configure appache by mapping Universal Resource Locaters (URL’s) to either R scripts or R functions. The R code relies on CGI variables to read a client request and R’s input/output facilities to write the response.
One advantage to Rapache’s architecture is robust multi-process management by Apache. In contrast to Rserve and RSOAP, Rapache is a pre-fork server utilizing HTTP as the communications protocol. Another advantage is a clear separation, a loose coupling, of R code from client code. With Rserve and RSOAP, the client must send data and R commands to be executed on the server. With Rapache the only client requirements are the ability to communicate via HTTP. Additionally, Rapache gains significant authentication, authorization, and encryption mechanism by virtue of being embedded in Apache.
Existing Demos of Architechture based on R Apache-
You can download version 1.1.10 of rApache now. There
are only two significant changes and you don’t have to edit your
apache config or change any code (just recompile rApache and
reinstall):
1) Error reporting should be more informative. both when you
accidentally introduce errors in the Apache config, and when your code
introduces warnings and errors from web requests.
I’ve struggled with this one for awhile, not really knowing what
strategy would be best. Basically, rApache hooks into the R I/O layer
at such a low level that it’s hard to capture all warnings and errors
as they occur and introduce them to the user in a sane manner. In
prior releases, when ROutputErrors was in effect (either the apache
directive or the R function) one would typically see a bunch of grey
boxes with a red outline with a title of RApache Warning/Error!!!.
Unfortunately those grey boxes could contain empty lines, one line of
error, or a few that relate to the lines in previously displayed
boxes. Really a big uninformative mess.
The new approach is to print just one warning box with the title
“”Oops!!! <b>rApache</b> has something to tell you. View source and
read the HTML comments at the end.” and then as the title implies you
can read the HTML comment located at the end of the file… after the
closing html. That way, you’re actually reading how R would present
the warnings and errors to you as if you executed the code at the R
command prompt. And if you don’t use ROutputErrors, the warning/error
messages are printed in the Apache log file, just as they were before,
but nicer 😉
2) Code dispatching has changed so please let me know if I’ve
introduced any strange behavior.
This was necessary to enhance error reporting. Prior to this release,
rApache would use R’s C API exclusively to build up the call to your
code that is then passed to R’s evaluation engine. The advantage to
this approach is that it’s much more efficient as there is no parsing
involved, however all information about parse errors, files which
produced errors, etc. were lost. The new approach uses R’s built-in
parse function to build up the call and then passes it of to R. A
slight overhead, but it should be negligible. So, if you feel that
this approach is too slow OR I’ve introduced bugs or strange behavior,
please let me know.
FUTURE PLANS
I’m gaining more experience building Debian/Ubuntu packages each day,
so hopefully by some time in 2011 you can rely on binary releases for
these distributions and not install rApache from source! Fingers
crossed!
Development on the rApache 1.1 branch will be winding down (save bug
fix releases) as I transition to the 1.2 branch. This will involve
taking out a small chunk of code that defines the rApache development
environment (all the CGI variables and the functions such as
setHeader, setCookie, etc) and placing it in its own R package…
unnamed as of yet. This is to facilitate my development of the ralite
R package, a small single user cross-platform web server.
The goal for ralite is to speed up development of R web applications,
take out a bit of friction in the development process by not having to
run the full rApache server. Plus it would allow users to develop in
the rApache enronment while on windows and later deploy on more
capable server environments. The secondary goal for ralite is it’s use
in other web server environments (nginx and IIS come to mind) as a
persistent per-client process.
And finally, wiki.rapache.net will be the new www.rapache.net once I
translate the manual over… any day now.
and as per http://cran.r-project.org/src/base/NEWS
the answer is plenty is new in the newR.
While you and me, were busy writing and reading blogs, or generally writing code for earning more money, or our own research- Uncle Peter D and his band of merry men have been really busy in a much more upgraded R.
————————————–
CHANGES————————-
NEW FEATURES:
• Reading a packages's CITATION file now defaults to ASCII rather
than Latin-1: a package with a non-ASCII CITATION file should
declare an encoding in its DESCRIPTION file and use that encoding
for the CITATION file.
• difftime() now defaults to the "tzone" attribute of "POSIXlt"
objects rather than to the current timezone as set by the default
for the tz argument. (Wish of PR#14182.)
• pretty() is now generic, with new methods for "Date" and "POSIXt"
classes (based on code contributed by Felix Andrews).
• unique() and match() are now faster on character vectors where
all elements are in the global CHARSXP cache and have unmarked
encoding (ASCII). Thanks to Matthew Dowle for suggesting
improvements to the way the hash code is generated in unique.c.
• The enquote() utility, in use internally, is exported now.
• .C() and .Fortran() now map non-zero return values (other than
NA_LOGICAL) for logical vectors to TRUE: it has been an implicit
assumption that they are treated as true.
• The print() methods for "glm" and "lm" objects now insert
linebreaks in long calls in the same way that the print() methods
for "summary.[g]lm" objects have long done. This does change the
layout of the examples for a number of packages, e.g. MASS.
(PR#14250)
• constrOptim() can now be used with method "SANN". (PR#14245)
It gains an argument hessian to be passed to optim(), which
allows all the ... arguments to be intended for f() and grad().
(PR#14071)
• curve() now allows expr to be an object of mode "expression" as
well as "call" and "function".
• The "POSIX[cl]t" methods for Axis() have been replaced by a
single method for "POSIXt".
There are no longer separate plot() methods for "POSIX[cl]t" and
"Date": the default method has been able to handle those classes
for a long time. This _inter alia_ allows a single date-time
object to be supplied, the wish of PR#14016.
The methods had a different default ("") for xlab.
• Classes "POSIXct", "POSIXlt" and "difftime" have generators
.POSIXct(), .POSIXlt() and .difftime(). Package authors are
advised to make use of them (they are available from R 2.11.0) to
proof against planned future changes to the classes.
The ordering of the classes has been changed, so "POSIXt" is now
the second class. See the document ‘Updating packages for
changes in R 2.12.x’ on for
the consequences for a handful of CRAN packages.
• The "POSIXct" method of as.Date() allows a timezone to be
specified (but still defaults to UTC).
• New list2env() utility function as an inverse of
as.list() and for fast multi-assign() to existing
environment. as.environment() is now generic and uses list2env()
as list method.
• There are several small changes to output which ‘zap’ small
numbers, e.g. in printing quantiles of residuals in summaries
from "lm" and "glm" fits, and in test statisics in print.anova().
• Special names such as "dim", "names", etc, are now allowed as
slot names of S4 classes, with "class" the only remaining
exception.
• File .Renviron can have architecture-specific versions such as
.Renviron.i386 on systems with sub-architectures.
• installed.packages() has a new argument subarch to filter on
sub-architecture.
• The summary() method for packageStatus() now has a separate
print() method.
• The default summary() method returns an object inheriting from
class "summaryDefault" which has a separate print() method that
calls zapsmall() for numeric/complex values.
• The startup message now includes the platform and if used,
sub-architecture: this is useful where different
(sub-)architectures run on the same OS.
• The getGraphicsEvent() mechanism now allows multiple windows to
return graphics events, through the new functions
setGraphicsEventHandlers(), setGraphicsEventEnv(), and
getGraphicsEventEnv(). (Currently implemented in the windows()
and X11() devices.)
• tools::texi2dvi() gains an index argument, mainly for use by R
CMD Rd2pdf.
It avoids the use of texindy by texinfo's texi2dvi >= 1.157,
since that does not emulate 'makeindex' well enough to avoid
problems with special characters (such as (, {, !) in indices.
• The ability of readLines() and scan() to re-encode inputs to
marked UTF-8 strings on Windows since R 2.7.0 is extended to
non-UTF-8 locales on other OSes.
• scan() gains a fileEncoding argument to match read.table().
• points() and lines() gain "table" methods to match plot(). (Wish
of PR#10472.)
• Sys.chmod() allows argument mode to be a vector, recycled along
paths.
• There are |, & and xor() methods for classes "octmode" and
"hexmode", which work bitwise.
• Environment variables R_DVIPSCMD, R_LATEXCMD, R_MAKEINDEXCMD,
R_PDFLATEXCMD are no longer used nor set in an R session. (With
the move to tools::texi2dvi(), the conventional environment
variables LATEX, MAKEINDEX and PDFLATEX will be used.
options("dvipscmd") defaults to the value of DVIPS, then to
"dvips".)
• New function isatty() to see if terminal connections are
redirected.
• summaryRprof() returns the sampling interval in component
sample.interval and only returns in by.self data for functions
with non-zero self times.
• print(x) and str(x) now indicate if an empty list x is named.
• install.packages() and remove.packages() with lib unspecified and
multiple libraries in .libPaths() inform the user of the library
location used with a message rather than a warning.
• There is limited support for multiple compressed streams on a
file: all of [bgx]zfile() allow streams to be appended to an
existing file, but bzfile() reads only the first stream.
• Function person() in package utils now uses a given/family scheme
in preference to first/middle/last, is vectorized to handle an
arbitrary number of persons, and gains a role argument to specify
person roles using a controlled vocabulary (the MARC relator
terms).
• Package utils adds a new "bibentry" class for representing and
manipulating bibliographic information in enhanced BibTeX style,
unifying and enhancing the previously existing mechanisms.
• A bibstyle() function has been added to the tools package with
default JSS style for rendering "bibentry" objects, and a
mechanism for registering other rendering styles.
• Several aspects of the display of text help are now customizable
using the new Rd2txt_options() function.
options("help_text_width") is no longer used.
• Added \href tag to the Rd format, to allow hyperlinks to URLs
without displaying the full URL.
• Added \newcommand and \renewcommand tags to the Rd format, to
allow user-defined macros.
• New toRd() generic in the tools package to convert objects to
fragments of Rd code, and added "fragment" argument to Rd2txt(),
Rd2HTML(), and Rd2latex() to support it.
• Directory R_HOME/share/texmf now follows the TDS conventions, so
can be set as a texmf tree (‘root directory’ in MiKTeX parlance).
• S3 generic functions now use correct S4 inheritance when
dispatching on an S4 object. See ?Methods, section on “Methods
for S3 Generic Functions†for recommendations and details.
• format.pval() gains a ... argument to pass arguments such as
nsmall to format(). (Wish of PR#9574)
• legend() supports title.adj. (Wish of PR#13415)
• Added support for subsetting "raster" objects, plus assigning to
a subset, conversion to a matrix (of colour strings), and
comparisons (== and !=).
• Added a new parseLatex() function (and related functions
deparseLatex() and latexToUtf8()) to support conversion of
bibliographic entries for display in R.
• Text rendering of \itemize in help uses a Unicode bullet in UTF-8
and most single-byte Windows locales.
• Added support for polygons with holes to the graphics engine.
This is implemented for the pdf(), postscript(),
x11(type="cairo"), windows(), and quartz() devices (and
associated raster formats), but not for x11(type="Xlib") or
xfig() or pictex(). The user-level interface is the polypath()
function in graphics and grid.path() in grid.
• File NEWS is now generated at installation with a slightly
different format: it will be in UTF-8 on platforms using UTF-8,
and otherwise in ASCII. There is also a PDF version, NEWS.pdf,
installed at the top-level of the R distribution.
• kmeans(x, 1) now works. Further, kmeans now returns between and
total sum of squares.
• arrayInd() and which() gain an argument useNames. For arrayInd,
the default is now false, for speed reasons.
• As is done for closures, the default print method for the formula
class now displays the associated environment if it is not the
global environment.
• A new facility has been added for inserting code into a package
without re-installing it, to facilitate testing changes which can
be selectively added and backed out. See ?insertSource.
• New function readRenviron to (re-)read files in the format of
~/.Renviron and Renviron.site.
• require() will now return FALSE (and not fail) if loading the
package or one of its dependencies fails.
• aperm() now allows argument perm to be a character vector when
the array has named dimnames (as the results of table() calls
do). Similarly, array() allows MARGIN to be a character vector.
(Based on suggestions of Michael Lachmann.)
• Package utils now exports and documents functions
aspell_package_Rd_files() and aspell_package_vignettes() for
spell checking package Rd files and vignettes using Aspell,
Ispell or Hunspell.
• Package news can now be given in Rd format, and news() prefers
these inst/NEWS.Rd files to old-style plain text NEWS or
inst/NEWS files.
• New simple function packageVersion().
• The PCRE library has been updated to version 8.10.
• The standard Unix-alike terminal interface declares its name to
readline as 'R', so that can be used for conditional sections in
~/.inputrc files.
• ‘Writing R Extensions’ now stresses that the standard sections in
.Rd files (other than \alias, \keyword and \note) are intended to
be unique, and the conversion tools now drop duplicates with a
warning.
The .Rd conversion tools also warn about an unrecognized type in
a \docType section.
• ecdf() objects now have a quantile() method.
• format() methods for date-time objects now attempt to make use of
a "tzone" attribute with "%Z" and "%z" formats, but it is not
always possible. (Wish of PR#14358.)
• tools::texi2dvi(file, clean = TRUE) now works in more cases (e.g.
where emulation is used and when file is not in the current
directory).
• New function droplevels() to remove unused factor levels.
• system(command, intern = TRUE) now gives an error on a Unix-alike
(as well as on Windows) if command cannot be run. It reports a
non-success exit status from running command as a warning.
On a Unix-alike an attempt is made to return the actual exit
status of the command in system(intern = FALSE): previously this
had been system-dependent but on POSIX-compliant systems the
value return was 256 times the status.
• system() has a new argument ignore.stdout which can be used to
(portably) ignore standard output.
• system(intern = TRUE) and pipe() connections are guaranteed to be
avaliable on all builds of R.
• Sys.which() has been altered to return "" if the command is not
found (even on Solaris).
• A facility for defining reference-based S4 classes (in the OOP
style of Java, C++, etc.) has been added experimentally to
package methods; see ?ReferenceClasses.
• The predict method for "loess" fits gains an na.action argument
which defaults to na.pass rather than the previous default of
na.omit.
Predictions from "loess" fits are now named from the row names of
newdata.
• Parsing errors detected during Sweave() processing will now be
reported referencing their original location in the source file.
• New adjustcolor() utility, e.g., for simple translucent color
schemes.
• qr() now has a trivial lm method with a simple (fast) validity
check.
• An experimental new programming model has been added to package
methods for reference (OOP-style) classes and methods. See
?ReferenceClasses.
• bzip2 has been updated to version 1.0.6 (bug-fix release).
--with-system-bzlib now requires at least version 1.0.6.
• R now provides jss.cls and jss.bst (the class and bib style file
for the Journal of Statistical Software) as well as RJournal.bib
and Rnews.bib, and R CMD ensures that the .bst and .bib files are
found by BibTeX.
• Functions using the TAR environment variable no longer quote the
value when making system calls. This allows values such as tar
--force-local, but does require additional quotes in, e.g., TAR =
"'/path with spaces/mytar'".
DEPRECATED & DEFUNCT:
• Supplying the parser with a character string containing both
octal/hex and Unicode escapes is now an error.
• File extension .C for C++ code files in packages is now defunct.
• R CMD check no longer supports configuration files containing
Perl configuration variables: use the environment variables
documented in ‘R Internals’ instead.
• The save argument of require() now defaults to FALSE and save =
TRUE is now deprecated. (This facility is very rarely actually
used, and was superseded by the Depends field of the DESCRIPTION
file long ago.)
• R CMD check --no-latex is deprecated in favour of --no-manual.
• R CMD Sd2Rd is formally deprecated and will be removed in R
2.13.0.
PACKAGE INSTALLATION:
• install.packages() has a new argument libs_only to optionally
pass --libs-only to R CMD INSTALL and works analogously for
Windows binary installs (to add support for 64- or 32-bit
Windows).
• When sub-architectures are in use, the installed architectures
are recorded in the Archs field of the DESCRIPTION file. There
is a new default filter, "subarch", in available.packages() to
make use of this.
Code is compiled in a copy of the src directory when a package is
installed for more than one sub-architecture: this avoid problems
with cleaning the sources between building sub-architectures.
• R CMD INSTALL --libs-only no longer overrides the setting of
locking, so a previous version of the package will be restored
unless --no-lock is specified.
UTILITIES:
• R CMD Rprof|build|check are now based on R rather than Perl
scripts. The only remaining Perl scripts are the deprecated R
CMD Sd2Rd and install-info.pl (used only if install-info is not
found) as well as some maintainer-mode-only scripts.
*NB:* because these have been completely rewritten, users should
not expect undocumented details of previous implementations to
have been duplicated.
R CMD no longer manipulates the environment variables PERL5LIB
and PERLLIB.
• R CMD check has a new argument --extra-arch to confine tests to
those needed to check an additional sub-architecture.
Its check for “Subdirectory 'inst' contains no files†is more
thorough: it looks for files, and warns if there are only empty
directories.
Environment variables such as R_LIBS and those used for
customization can be set for the duration of checking _via_ a
file ~/.R/check.Renviron (in the format used by .Renviron, and
with sub-architecture specific versions such as
~/.R/check.Renviron.i386 taking precedence).
There are new options --multiarch to check the package under all
of the installed sub-architectures and --no-multiarch to confine
checking to the sub-architecture under which check is invoked.
If neither option is supplied, a test is done of installed
sub-architectures and all those which can be run on the current
OS are used.
Unless multiple sub-architectures are selected, the install done
by check for testing purposes is only of the current
sub-architecture (_via_ R CMD INSTALL --no-multiarch).
It will skip the check for non-ascii characters in code or data
if the environment variables _R_CHECK_ASCII_CODE_ or
_R_CHECK_ASCII_DATA_ are respectively set to FALSE. (Suggestion
of Vince Carey.)
• R CMD build no longer creates an INDEX file (R CMD INSTALL does
so), and --force removes (rather than overwrites) an existing
INDEX file.
It supports a file ~/.R/build.Renviron analogously to check.
It now runs build-time \Sexpr expressions in help files.
• R CMD Rd2dvi makes use of tools::texi2dvi() to process the
package manual. It is now implemented entirely in R (rather than
partially as a shell script).
• R CMD Rprof now uses utils::summaryRprof() rather than Perl. It
has new arguments to select one of the tables and to limit the
number of entries printed.
• R CMD Sweave now runs R with --vanilla so the environment setting
of R_LIBS will always be used.
C-LEVEL FACILITIES:
• lang5() and lang6() (in addition to pre-existing lang[1-4]())
convenience functions for easier construction of eval() calls.
If you have your own definition, do wrap it inside #ifndef lang5
.... #endif to keep it working with old and new R.
• Header R.h now includes only the C headers it itself needs, hence
no longer includes errno.h. (This helps avoid problems when it
is included from C++ source files.)
• Headers Rinternals.h and R_ext/Print.h include the C++ versions
of stdio.h and stdarg.h respectively if included from a C++
source file.
INSTALLATION:
• A C99 compiler is now required, and more C99 language features
will be used in the R sources.
• Tcl/Tk >= 8.4 is now required (increased from 8.3).
• System functions access, chdir and getcwd are now essential to
configure R. (In practice they have been required for some
time.)
• make check compares the output of the examples from several of
the base packages to reference output rather than the previous
output (if any). Expect some differences due to differences in
floating-point computations between platforms.
• File NEWS is no longer in the sources, but generated as part of
the installation. The primary source for changes is now
doc/NEWS.Rd.
• The popen system call is now required to build R. This ensures
the availability of system(intern = TRUE), pipe() connections and
printing from postscript().
• The pkg-config file libR.pc now also works when R is installed
using a sub-architecture.
• R has always required a BLAS that conforms to IE60559 arithmetic,
but after discovery of more real-world problems caused by a BLAS
that did not, this is tested more thoroughly in this version.
BUG FIXES:
• Calls to selectMethod() by default no longer cache inherited
methods. This could previously corrupt methods used by as().
• The densities of non-central chi-squared are now more accurate in
some cases in the extreme tails, e.g. dchisq(2000, 2, 1000), as a
series expansion was truncated too early. (PR#14105)
• pt() is more accurate in the left tail for ncp large, e.g.
pt(-1000, 3, 200). (PR#14069)
• The default C function (R_binary) for binary ops now sets the S4
bit in the result if either argument is an S4 object. (PR#13209)
• source(echo=TRUE) failed to echo comments that followed the last
statement in a file.
• S4 classes that contained one of "matrix", "array" or "ts" and
also another class now accept superclass objects in new(). Also
fixes failure to call validObject() for these classes.
• Conditional inheritance defined by argument test in
methods::setIs() will no longer be used in S4 method selection
(caching these methods could give incorrect results). See
?setIs.
• The signature of an implicit generic is now used by setGeneric()
when that does not use a definition nor explicitly set a
signature.
• A bug in callNextMethod() for some examples with "..." in the
arguments has been fixed. See file
src/library/methods/tests/nextWithDots.R in the sources.
• match(x, table) (and hence %in%) now treat "POSIXlt" consistently
with, e.g., "POSIXct".
• Built-in code dealing with environments (get(), assign(),
parent.env(), is.environment() and others) now behave
consistently to recognize S4 subclasses; is.name() also
recognizes subclasses.
• The abs.tol control parameter to nlminb() now defaults to 0.0 to
avoid false declarations of convergence in objective functions
that may go negative.
• The standard Unix-alike termination dialog to ask whether to save
the workspace takes a EOF response as n to avoid problems with a
damaged terminal connection. (PR#14332)
• Added warn.unused argument to hist.default() to allow suppression
of spurious warnings about graphical parameters used with
plot=FALSE. (PR#14341)
• predict.lm(), summary.lm(), and indeed lm() itself had issues
with residual DF in zero-weighted cases (the latter two only in
connection with empty models). (Thanks to Bill Dunlap for
spotting the predict() case.)
• aperm() treated resize = NA as resize = TRUE.
• constrOptim() now has an improved convergence criterion, notably
for cases where the minimum was (very close to) zero; further,
other tweaks inspired from code proposals by Ravi Varadhan.
• Rendering of S3 and S4 methods in man pages has been corrected
and made consistent across output formats.
• Simple markup is now allowed in \title sections in .Rd files.
• The behaviour of as.logical() on factors (to use the levels) was
lost in R 2.6.0 and has been restored.
• prompt() did not backquote some default arguments in the \usage
section. (Reported by Claudia Beleites.)
• writeBin() disallows attempts to write 2GB or more in a single
call. (PR#14362)
• new() and getClass() will now work if Class is a subclass of
"classRepresentation" and should also be faster in typical calls.
• The summary() method for data frames makes a better job of names
containing characters invalid in the current locale.
• [[ sub-assignment for factors could create an invalid factor
(reported by Bill Dunlap).
• Negate(f) would not evaluate argument f until first use of
returned function (reported by Olaf Mersmann).
• quietly=FALSE is now also an optional argument of library(), and
consequently, quietly is now propagated also for loading
dependent packages, e.g., in require(*, quietly=TRUE).
• If the loop variable in a for loop was deleted, it would be
recreated as a global variable. (Reported by Radford Neal; the
fix includes his optimizations as well.)
• Task callbacks could report the wrong expression when the task
involved parsing new code. (PR#14368)
• getNamespaceVersion() failed; this was an accidental change in
2.11.0. (PR#14374)
• identical() returned FALSE for external pointer objects even when
the pointer addresses were the same.
• L$a@x[] <- val did not duplicate in a case it should have.
• tempfile() now always gives a random file name (even if the
directory is specified) when called directly after startup and
before the R RNG had been used. (PR#14381)
• quantile(type=6) behaved inconsistently. (PR#14383)
• backSpline(.) behaved incorrectly when the knot sequence was
decreasing. (PR#14386)
• The reference BLAS included in R was assuming that 0*x and x*0
were always zero (whereas they could be NA or NaN in IEC 60559
arithmetic). This was seen in results from tcrossprod, and for
example that log(0) %*% 0 gave 0.
• The calculation of whether text was completely outside the device
region (in which case, you draw nothing) was wrong for screen
devices (which have [0, 0] at top-left). The symptom was (long)
text disappearing when resizing a screen window (to make it
smaller). (PR#14391)
• model.frame(drop.unused.levels = TRUE) did not take into account
NA values of factors when deciding to drop levels. (PR#14393)
• library.dynam.unload required an absolute path for libpath.
(PR#14385)
Both library() and loadNamespace() now record absolute paths for
use by searchpaths() and getNamespaceInfo(ns, "path").
• The self-starting model NLSstClosestX failed if some deviation
was exactly zero. (PR#14384)
• X11(type = "cairo") (and other devices such as png using
cairographics) and which use Pango font selection now work around
a bug in Pango when very small fonts (those with sizes between 0
and 1 in Pango's internal units) are requested. (PR#14369)
• Added workaround for the font problem with X11(type = "cairo")
and similar on Mac OS X whereby italic and bold styles were
interchanged. (PR#13463 amongst many other reports.)
• source(chdir = TRUE) failed to reset the working directory if it
could not be determined - that is now an error.
• Fix for crash of example(rasterImage) on x11(type="Xlib").
• Force Quartz to bring the on-screen display up-to-date
immediately before the snapshot is taken by grid.cap() in the
Cocoa implementation. (PR#14260)
• model.frame had an unstated 500 byte limit on variable names.
(Example reported by Terry Therneau.)
• The 256-byte limit on names is now documented. • Subassignment by [, [[ or $ on an expression object with value
NULL coerced the object to a list.