[此贴子已经被作者于2009-3-4 10:29:20编辑过]
还有一篇,全文转载:
![]() ![]() January 8, 2009, 1:52 pm My story Also of note, the software is open source, meaning people can pick it up for free and make their own changes to the code. Such flexibility has inspired statistically minded people of all stripes to get behind R and make it a real success story. Most of the people reacting to the story expressed pleasure at seeing R receive mainstream attention. People chimed in with the unique ways they’re using the technology. Vhayu Technologies talked There were also some complaints that my story did not focus enough on S, which was a precursor to R developed at Bell Labs. John Chambers, now a consulting professor of statistics at Stanford University, drove much of the early S work at Bell Labs and talked with me at length about S and R. Without question, R arrived as a result of the fine work done with S, but it’s the rapid rise of R, helped by its open-source nature, that has proved so gripping. Speaking of R, Mr. Chambers said, “It’s way beyond anything we could have imagined at Bell Labs.” If you’d like some more of S’s history, you’ll find it at the end of Mr. Chambers’s new book, “Software for Data Analysis In addition, the commercial potential of R is worth some further discussion. Pfizer was a prominent R user mentioned in the story. The company relies on R for its nonclinical drug studies and has shied away from using the technology for clinical research that will ultimately be presented to regulators. For such work, Pfizer instead turns to software from SAS Institute, which brings in more than $2 billion a year in revenue from data analytics software and services. Were Pfizer to use R in clinical studies, it would run the risk of seeing its research questioned or even rejected by regulators doubting the veracity of results based on what they view as an unknown quantity. “It’s very hard to displace the industry standard in those types of cases,” said Max Kuhn, associate director of nonclinical statistics at Pfizer. Of course, the Linux operating system over the course of many years has managed to rise from an unknown entity to one that has gained top approval from governments around the world for everything from handling top-secret files to being used for processing tax data. So we’ll see what happens with R in the long run. Revolution Computing While the base software is free, Revolution offers ways to speed up the software on certain applications and to run it on large computers. In addition, Revolution provides support services to customers like Pfizer and Bank of America. Intel’s venture capital arm invested in Revolution last year. Lastly, some readers had questions on exactly how many people use R. A number of people interviewed, including those who work most closely with the software, estimated the R population at 250,000. Intel Capital has placed the number of R users at 1 million, and Revolution kicks the estimate all the way up to 2 million. Such disparity often accompanies open-source projects, where it’s difficult to tell just how far a piece of software’s tentacles spread and how active the users really, um, R. |
R is one of the fastest open source data analysis packages. Since it is free and provides many additional packages for all kind of statistics, we warmly recommend it. |
问一个问题
到底什么样的人需要学r
现在软件这么多,学的专业也不同。
现在谈论R、sas、spss的多,但是国外许多大学还用GAUSS、stata这些,
我现在用的主要的3个统计软件是R,SAS 和MATLAB, R 和MATLAB在程序编排上有很多相似之处。 我有在R 里面写过像rref (reduce row echolon form)这样的matlab functioin,编写的时候结构是一样的。2者相对着学很有好处。
SAS对处理huge data的好处是显而易见的,速度极快。 不过programming的语言比较非传统,东西太多了。每个不同的manual都有好几百页甚至上千页。学起来太累了。不过现在上班必须用SAS我也没办法。
从大学一年级开始用MATLAB,二年级开始用 R,三年级开始用SAS, 到现在工作了, R和MATLAB是用的最多的。
R 和 MATLAB在computational statistics方面的优势是相当的。
R 我用的最多的就是在linear model, GLM, Time Series ,survival and computer intensive.
MATLAB 用的最多的是在multivariate and computer intensive.
SAS 的话 统计方面用的不太多确实。目前为止 categorical,longitudinal还有survival.
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请问上面四楼的大侠在哪儿工作啊? 因为你说你上班必须要使用SAS。 谢谢
R is developed by University of Auckland, where I studied Stats.
Great software really. We basically use it for each assignment from the very beginning to the end.