TC_Chu's Point

R, now a major programming language

As a language specifically for data analysis, R isn't in the same league in raw sales as general-purpose languages like C++ or Java, but it does show the most growth of any major language: R is the bright green box in the bottom row of the treemap above. Amongst print book sales for functional languages, R is both the biggest seller and the fastest growing by a large margin (as shown in thechart at 00:29 in this video about functional languages).

via R-Blogger

How to download complete XML records from PubMed and extract data

How it works

What’s cool about esearch is that you can tell it to save a history of the articles found by your query, and then use another function called efetch to download that history. This is done by adding &usehistory=y to your search, which will generate this XML (in addition to some other XML-tags):

<WebEnv>
NCID_1_90555773_130.14.18.48_5553_1335519406_1226217114
</WebEnv>

Once we have extracted the WebEnv string, we just tell PubMed’s efetch to send us the articles saved in WebEnv. There’s one complication, though. PubMed “only” allows us to fetch 10 000 articles in one go, therefore my code includes a loop that will batch download the data, and paste it together in order to create valid XML-code. The XML cutting and pasting is done with gsub, since the unparsed XML-data is just a long string. It’s not the most beautiful solution, but it seems to work.

Now that all XML-data is saved in one object, we just need to parse it an extract whatever PubMed field(s) we’re interested in. I’ve included a function that will parse the XML-code and extract journal counts, although you could use the same method to extract any field.

原文連結 http://www.r-bloggers.com/how-to-download-complete-xml-records-from-pubmed-and-extract-data

 

118 years of US State Weather Data

A recent post on the Junkcharts blog looked at US weather dataand the importance of explaining scales (which in this case went up to 118). Ultimately, it turns out that 118 is the rank of the data compared to the previous 117 years of data (in ascending order, so that 118 is the highest). At the end of the post,

via R-Blogger

Visualising the Path of a Genetic Algorithm

We quite regularly use genetic algorithms to optimise over the ad-hoc functions we develop when trying to solve problems in applied mathematics. However it’s a bit disconcerting to have your algorithm roam through a high dimensional solution space while not being able to picture what it’s doing or how close one solution is to another. With this in mind, and also just out of curiosity, I’ve tried to visualise the path of a genetic algorithm by using principal components analysis.

via R-Blogger

Getting Historical Weather Data in R and SAP HANA

  Now, to get historical weather data, I am using Weather Underground's REST APIs and I put together a simple program in R to get the weather data in a data.frame.  This R module gets called from SAP HANA and it inserts a new table into HANA with the right weather information.  Once, I have the data in HANA, I performed mash-ups in HANA and off I go on my intellectual pursuit.

via R-Blogger

R Statistics Mobile Console (iPhone)

http://www.cloudstat.org/

R Tutorial

Tutorials

• Stats202 class
• R intro
• R fundamentals
• R data import/export
• R-bloggers
• Web app integration

http://www.rcasts.com/2012/03/data-analysis-training.html

 

中華R軟體學會

https://sites.google.com/site/zhonghuarruantixuehui/home

http://www.r-software.org/ <-- New WebSite

An Intro to Ensemble Learning in R

To create our initial ensemble, we will use the linear model, and a random forest. A random forest can be a powerful learning technique. It creates multiple decision trees from randomized sets of predictors and observations. It will be less useful here, as we only have three predictors, but will still illustrate the general point.

via R-Blogger

A Weather API Designed for Developers

http://www.wunderground.com/weather/api/ <---應該有些好玩的資料可以玩

另外台灣的氣象資料網站 http://dbar.ttfri.narl.org.tw/Default.aspx <---這個就不用去了 因為申請了也沒下文!!!

R is Ready for Business

http://www.revolutionanalytics.com/

Oracle's Big Data Appliance to include R

The Big Data Appliance also includes the R programming language, a popular open source statistical-analysis tool. This R engine will integrate with 11g R2, so presumably if you want to do statistical analysis on unstructured data stored in and chewed by Hadoop, you will have to move it to Oracle after the chewing has subsided.

via RevolutionAnalytics

'Big Data' Means Business Needs Mathematicians

As Carnegie Mellon statistician Cosma Shaliz points out, O'Neill's description of the skills required of a data scientist are precisely those of a suitably well-educated statistician, even if he or she has only an undergraduate degree in the subject. Granted, Shaliz teaches at Carnegie Mellon, which is among the best engineering schools on the planet, so that's not to say that everyone with a B.S. in statistics has mastered modern regression, advanced data analysis, data mining and statistical visualization.

This re-branding of statistical literacy as "data science" points out a larger trend -- disciplines that were formerly the domain of the specialist, such as statistics, are now more important than to a larger segment of the business world than ever. The fact that so few students view even a fraction of this level of mastery as necessary -- and that schools often do not offer even a basic statistical education to non math majors until the post-graduate level -- suggests that in this area, perhaps even more than other areas associated with engineering, there is a yawning gap between the skills our workforce possesses and the skills employers require.

via MIT Technology Review

各位ㄚ 統計學將成為顯學啦 大家來學R

KDNuggest: R most commonly used software for data mining & analytics

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Learn R Quickly !

If you currently use another statistical package, why learn R?

1. It's free! If you are a teacher or a student, the benefits are obvious.
2. It runs on a variety of platforms including Windows, Unix and MacOS.
3. It provides an unparalleled platform for programming new statistical methods in an easy and straightforward manner.
4. It contains advanced statistical routines not yet available in other packages.
5. It has state-of-the-art graphics capabilities.

http://www.statmethods.net/

不錯的R學習網站 書也不錯 很實用

RStudio available at cloudnumbers.com

RStudio™ is an integrated development environment (IDE) for the statistical software R (www.r-project.org). It combines an intuitive user interface with powerful coding tools to help you get the most out of R.

cloudnumbers.com provides researchers and companies with the access to resources to perform high performance calculations in the cloud. One often used application at cloudnumbers.com’s computer clusters in the cloud is the statistical software R.

via R-Blogger

10 reasons why a grad student should use R

Kevin Goulding is working on a Master’s degree in Applied Economics at Montana State University, and offers 10 reasons why grad students should choose R for statistical analyses, homework problems, and thesis research:

• R is free, and lets grad students escape the burdens of commercial license costs.
• R has really good online documentation; and the community is unparalleled.  
• The command-line interface is perfect for learning by doing. 
• R is on the cutting edge, and expanding rapidly.
• The R programming language is intuitive.  
• R creates stunning visuals. 
• R and LaTeX work together — seamlessly. 
• R is used by practitioners in a plethora of academic disciplines. 
• R makes you think.  
• There’s always more than one way to accomplish something.

via R-Blogger