UseR 2012 Early Registration #rstats

Early Registration Deadline Approaches for UseR 2012

http://biostat.mc.vanderbilt.edu/wiki/Main/UseR-2012

Registration

 

Deadlines

  • Early Registration: Jan 23 24 – Feb 29
  • Regular Registration: Mar 1 – May 12
  • Late Registration: May 13 – June 4
  • On-site Registration: June 12 – June 15

 

Fees

Academic Non-Academic Student/Retiree
Registration: Early $290 $440 $145
Registration: Regular $365 $560 $185
Registration: Late $435 $645 $225
Registration: On-site $720 $720 $360
Short Course $200 $300 $100

 

useR 2012

The 8th International R Users Meeting

Vanderbilt University; Nashville, Tennessee, USA

12th-15th June 2012

http://biostat.mc.vanderbilt.edu/wiki/Main/UseR-2012

Morning
Terri Scott & Frank Harrell Reproducible Research with R, LaTeX, & Sweave
Uwe Ligges Writing efficient and parallel code in R
Dirk Eddelbuettel & Romain Francois Introduction to Rcpp
Douglas Bates Fitting and evaluating mixed models using lme4
Jeremiah Rounds RHIPE: R and Hadoop Integrated Programming Environment
Jeffrey Horner Building R Web Applications with Rook
Brandon Whitcher, Jorg Polzehl, & Karsten Tabelow Medical Image Analysis in R
Richard Heiberger & Martin Maechler Emacs Speaks Statistics
Olivia Lau A Crash Course in R Programming
Afternoon
Hadley Wickham Creating effective visualisations
Josh Paulson, JJ Allaire, & Joe Cheng Getting the Most Out of RStudio
Romain Francois & Dirk Eddelbuettel Advanced Rcpp Usage
Terry Therneau Design of the Survival Packages
Martin Morgan Bioconductor for High-Throughput Sequence Analysis
Max Kuhn Predictive Modeling with R and the caret Package
Robert Muenchen Managing Data with R
Barry Rowlingson Geospatial Data in R and Beyond
Karim Chine Cloud Computing for the R environment

 

Contact

Stephania McNeal-Goddard
Assistant to the Chair
stephania.mcneal-goddard@vanderbilt.edu
Phone: 615.322.2768
Fax: 615.343.4924
Vanderbilt University School of Medicine
Department of Biostatistics
S-2323 Medical Center North
Nashville, TN 37232-2158

Interview JJ Allaire Founder, RStudio

Here is an interview with JJ Allaire, founder of RStudio. RStudio is the IDE that has overtaken other IDE within the R Community in terms of ease of usage. On the eve of their latest product launch, JJ talks to DecisionStats on RStudio and more.

Ajay-  So what is new in the latest version of RStudio and how exactly is it useful for people?

JJ- The initial release of RStudio as well as the two follow-up releases we did last year were focused on the core elements of using R: editing and running code, getting help, and managing files, history, workspaces, plots, and packages. In the meantime users have also been asking for some bigger features that would improve the overall work-flow of doing analysis with R. In this release (v0.95) we focused on three of these features:

Projects. R developers tend to have several (and often dozens) of working contexts associated with different clients, analyses, data sets, etc. RStudio projects make it easy to keep these contexts well separated (with distinct R sessions, working directories, environments, command histories, and active source documents), switch quickly between project contexts, and even work with multiple projects at once (using multiple running versions of RStudio).

Version Control. The benefits of using version control for collaboration are well known, but we also believe that solo data analysis can achieve significant productivity gains by using version control (this discussion on Stack Overflow talks about why). In this release we introduced integrated support for the two most popular open-source version control systems: Git and Subversion. This includes changelist management, file diffing, and browsing of project history, all right from within RStudio.

Code Navigation. When you look at how programmers work a surprisingly large amount of time is spent simply navigating from one context to another. Modern programming environments for general purpose languages like C++ and Java solve this problem using various forms of code navigation, and in this release we’ve brought these capabilities to R. The two main features here are the ability to type the name of any file or function in your project and go immediately to it; and the ability to navigate to the definition of any function under your cursor (including the definition of functions within packages) using a keystroke (F2) or mouse gesture (Ctrl+Click).

Ajay- What’s the product road map for RStudio? When can we expect the IDE to turn into a full fledged GUI?

JJ- Linus Torvalds has said that “Linux is evolution, not intelligent design.” RStudio tries to operate on a similar principle—the world of statistical computing is too deep, diverse, and ever-changing for any one person or vendor to map out in advance what is most important. So, our internal process is to ship a new release every few months, listen to what people are doing with the product (and hope to do with it), and then start from scratch again making the improvements that are considered most important.

Right now some of the things which seem to be top of mind for users are improved support for authoring and reproducible research, various editor enhancements including code folding, and debugging tools.

What you’ll see is us do in a given release is to work on a combination of frequently requested features, smaller improvements to usability and work-flow, bug fixes, and finally architectural changes required to support current or future feature requirements.

While we do try to base what we work on as closely as possible on direct user-feedback, we also adhere to some core principles concerning the overall philosophy and direction of the product. So for example the answer to the question about the IDE turning into a full-fledged GUI is: never. We believe that textual representations of computations provide fundamental advantages in transparency, reproducibility, collaboration, and re-usability. We believe that writing code is simply the right way to do complex technical work, so we’ll always look for ways to make coding better, faster, and easier rather than try to eliminate coding altogether.

Ajay -Describe your journey in science from a high school student to your present work in R. I noticed you have been very successful in making software products that have been mostly proprietary products or sold to companies.

Why did you get into open source products with RStudio? What are your plans for monetizing RStudio further down the line?

JJ- In high school and college my principal areas of study were Political Science and Economics. I also had a very strong parallel interest in both computing and quantitative analysis. My first job out of college was as a financial analyst at a government agency. The tools I used in that job were SAS and Excel. I had a dim notion that there must be a better way to marry computation and data analysis than those tools, but of course no concept of what this would look like.

From there I went more in the direction of general purpose computing, starting a couple of companies where I worked principally on programming languages and authoring tools for the Web. These companies produced proprietary software, which at the time (between 1995 and 2005) was a workable model because it allowed us to build the revenue required to fund development and to promote and distribute the software to a wider audience.

By 2005 it was however becoming clear that proprietary software would ultimately be overtaken by open source software in nearly all domains. The cost of development had shrunken dramatically thanks to both the availability of high-quality open source languages and tools as well as the scale of global collaboration possible on open source projects. The cost of promoting and distributing software had also collapsed thanks to efficiency of both distribution and information diffusion on the Web.

When I heard about R and learned more about it, I become very excited and inspired by what the project had accomplished. A group of extremely talented and dedicated users had created the software they needed for their work and then shared the fruits of that work with everyone. R was a platform that everyone could rally around because it worked so well, was extensible in all the right ways, and most importantly was free (as in speech) so users could depend upon it as a long-term foundation for their work.

So I started RStudio with the aim of making useful contributions to the R community. We started with building an IDE because it seemed like a first-rate development environment for R that was both powerful and easy to use was an unmet need. Being aware that many other companies had built successful businesses around open-source software, we were also convinced that we could make RStudio available under a free and open-source license (the AGPLv3) while still creating a viable business. At this point RStudio is exclusively focused on creating the best IDE for R that we can. As the core product gets where it needs to be over the next couple of years we’ll then also begin to sell other products and services related to R and RStudio.

About-

http://rstudio.org/docs/about

Jjallaire

JJ Allaire

JJ Allaire is a software engineer and entrepreneur who has created a wide variety of products including ColdFusion,Windows Live WriterLose It!, and RStudio.

From http://en.wikipedia.org/wiki/Joseph_J._Allaire
In 1995 Joseph J. (JJ) Allaire co-founded Allaire Corporation with his brother Jeremy Allaire, creating the web development tool ColdFusion.[1] In March 2001, Allaire was sold to Macromedia where ColdFusion was integrated into the Macromedia MX product line. Macromedia was subsequently acquired by Adobe Systems, which continues to develop and market ColdFusion.
After the sale of his company, Allaire became frustrated at the difficulty of keeping track of research he was doing using Google. To address this problem, he co-founded Onfolio in 2004 with Adam Berrey, former Allaire co-founder and VP of Marketing at Macromedia.
On March 8, 2006, Onfolio was acquired by Microsoft where many of the features of the original product are being incorporated into the Windows Live Toolbar. On August 13, 2006, Microsoft released the public beta of a new desktop blogging client called Windows Live Writer that was created by Allaire’s team at Microsoft.
Starting in 2009, Allaire has been developing a web-based interface to the widely used R technical computing environment. A beta version of RStudio was publicly released on February 28, 2011.
JJ Allaire received his B.A. from Macalester College (St. Paul, MN) in 1991.
RStudio-

RStudio is an integrated development environment (IDE) for R which works with the standard version of R available from CRAN. Like R, RStudio is available under a free software license. RStudio is designed to be as straightforward and intuitive as possible to provide a friendly environment for new and experienced R users alike. RStudio is also a company, and they plan to sell services (support, training, consulting, hosting) related to the open-source software they distribute.

Some Ways Anonymous Could Disrupt the Internet if SOPA is passed

This is a piece of science fiction. I wrote while reading Isaac Assimov’s advice to writers in GOLD, while on a beach in Anjuna.

1) Identify senators, lobbyists, senior executives of companies advocating for SOPA. Go for selective targeting of these people than massive Denial of Service Attacks.

This could also include election fund raising websites in the United States.

2) Create hacking tools with simple interfaces to probe commonly known software errors, to enable wider audience including the Occupy Movement students to participate in hacking. thus making hacking more democratic. What are the top 25 errors as per  http://cwe.mitre.org/cwss/

http://www.decisionstats.com/top-25-most-dangerous-software-errors/ ?

 

Easy interface tools to check vulnerabilities would be the next generation to flooding tools like HOIC, LOIC – Massive DDOS atttacks make good press coverage but not so good technically

3) Disrupt digital payment mechanisms for selected targets (in step1) using tools developed in Step 2, and introduce random noise errors in payment transfers.

4) Help create a better secure internet by embedding Tor within Chromium with all tools for anonymity embedded for easy usage – a more secure peer to peer browser (like a mashup of Opera , tor and chromium).

or maybe embed bit torrents within a browser.

5) Disrupt media companies and cloud computing based companies like iTunes, Spotify or Google Music, just like virus, ant i viruses disrupted the desktop model of computing. After that offer solutions to the problems like companies of anti virus software did for decades.

6) Hacking websites is fine fun, but hacking internet databases and massively parallel data scrapers can help disrupt some of the status quo.

This applies to databases that offer data for sale, like credit bureaus etc. Making this kind of data public will eliminate data middlemen.

7) Use cross border, cross country regulatory arbitrage for better risk control of hacker attacks.

8) recruiting among universities using easy to use hacking tools to expand the pool of dedicated hacker armies.

9) using operations like those targeting child pornography to increase political acceptability of the hacker sub culture. Refrain from overtly negative and unimaginative bad Press Relations

10) If you cant convince  them to pass SOPA, confuse them 😉 Use bots for random clicks on ads to confuse internet commerce.

 

December Snowflakes R 2.14.1

Almost missed this one due to Christmas-

R 2.14.1 is out, and so are binaries

so download them here (winduh users!)

http://cran.r-project.org/bin/windows/base/

David S sums it all up here

http://blog.revolutionanalytics.com/2011/12/r-2141-is-released.html

This update makes a few small improvements (such as the ability to accurately count the number of available cores for parallel processing on Solaris and Windows, and improved support of grayscale Postscript and PDF graphics export) and fixes a few minor bugs (such as a correction to BIC calculations in the presence of zero-weight observations).

Binaries are here-

http://cran.r-project.org/bin/windows/base/R-2.14.1-win.exe

Prof Peter D speeaks here-

https://stat.ethz.ch/pipermail/r-announce/2011/000548.html

Changes in recent versions are here-

http://cran.r-project.org/bin/windows/base/CHANGES.R-2.14.1.html

Major Changes-

Direct support in R is starting with release 2.14.0 for High Performance Computing 

 

 

HANA Oncolyzer

An interesting use case of technology for better health is HANA Oncolyzer at http://epic.hpi.uni-potsdam.de/Home/HanaOncolyzer

“Build on the newest in-memory technology the HANA Oncolyzer is able to analyze even huge amounts of medical data in shortest time”, says Dr. Alexander Zeier, Deputy Chair of EPIC. Research institutes and university hospital support from HANA Oncolyzer by building the basis for a flexible exchange of information about efficiency of medicines and treatments.

In near future, the tumor’s DNA of all cancer patients needs to be analyzed to support specific patient therapies. These analyses result in medical data in amount of multiple terabytes. “These data need to be analyzed regarding mutations and anomalies in real-time”, says Matthias Steinbrecher at SAP’s Innovation Center in Potsdam. As one of the aims the research prototype HANA Oncolyzer was developed at our chair in cooperation with SAP’s Innovation Center in Potsdam. “The ‘heart’ of our development builds the in-memory technology that supports the parallel analysis of million of data within seconds in main memory”, saysMatthieu Schapranow, Ph.D. cand. at the HPI.

and

research activities result in 500.000 or more data points per patient.

and

With the help of a dedicated iPad application medical doctors can access all data mobile at any location anytime.

 

Interesting announcement from PiCloud

An interesting announcement from PiCloud who is a cloud computing startup, but focused on python (as the name suggests). They basically have created a cloud library (or in R lingo – a package) that enables you to call cloud power sitting from the desktop interface itself. This announcement is for multiple IP addresses. Real parallel processing or just a quick trick in technical jargon- you decide!

  1. Prepare
  2. Run
  3. Monitor
Prepare

s1 cores are comparable in performance to c1 cores with one extra trick up their sleeve: each job running in parallel will have a different IP.

Why is this important?
Using unique IPs is necessary to minimize the automated throttling most sites will impose when seeing fast, repeated access from a single IP.

How do I use it?
If you’re already using our c1 cores, all you’ll need to do is set the _type keyword.

cloud.call(func, _type=’s1′)

How much?
$0.04/core/hour

Why don’t other cores have individual IPs?
For other core types, such as c2, multiple cores may be running on a single machine that is assigned only a single IP address. When using s1 cores, you’re guaranteed that each core sits on a different machine.

 

http://www.picloud.com/

Revolution #Rstats Webinar

David Smith of Revo presents a nice webinar on the capabilities and abilities of Revolution R- if you are R curious and wonder how the commercial version has matured- you may want to take a look.

click below to view an executive Webinar

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Revolution R Enterprise—presented by author and blogger David Smith:

Revolution R: 100% R and More
On-Demand Webinar

This Webinar covers how R users can upgrade to:

  • Multi-processor speed improvements and parallel processing
  • Productivity and debugging with an integrated development environment (IDE) for the R language
  • “Big Data” analysis, with out-of-memory storage of multi-gigabyte data sets
  • Web Services for R, to integrate R computations and graphics into 3rd-Party applications like Excel and BI Dashboards
  • Expert technical support and consulting services for R

This webinar will be of value to current R users who want to learn more about the additional capabilities of Revolution R Enterprise to enhance the productivity, ease of use, and enterprise readiness of open source R. R users in academia will also find this webinar valuable: we will explain how all members of the academic community can obtain Revolution R Enterprise free of charge.

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contact -1-855-GET-REVO or via online form.
info@revolutionanalytics.com | (650) 330-0553 | Twitter @RevolutionR