Monthly Archives: January 2013

(Semi-)automating the R markdown to blogger workflow

January 2, 2013
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In his recent post 100 most read R posts for 2012 (stats from R-bloggers) – big data, visualization, data manipulation, and other languages Tal Galili - the guy behind R-Bloggers - presents his wishlist for 2013. Among other things he states &ldquo...

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100 most read R posts in 2012 (stats from R-bloggers) – big data, visualization, data manipulation, and other languages

January 2, 2013
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100 most read R posts in 2012 (stats from R-bloggers) – big data, visualization, data manipulation, and other languages

R-bloggers.com is now three years young. The site is an (unofficial) online journal of the R statistical programming environment, written by bloggers who agreed to contribute their R articles to the site. Last year, I posted on the top 24...

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R version 3 scheduled for April

January 2, 2013
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Ringing in the New Year, Peter Dalgaard announced yesterday on behalf of the entire R Core Team that the R language will graduate to Version 3 around April 1. This is only the third time that R has incremented its primary version number. Version 1.0.0 (released on February 29, 2000) was the first version deemed stable for production use....

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Just another R blog

January 2, 2013
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New year, new resolutions. This year, as a personal challenge, I decided to create a blog where I could share (and also receive) some tricks and tips about R programming language. The main motivation behind this blog is to learn how to use Knitr (http://yihui.name/knitr/). While I'm very concerned about the importance of...

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The (near) Future of Data Analysis – A Review

January 2, 2013
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The (near) Future of Data Analysis – A Review

Sean Murphy co-organizes Data Business DC, among many other things. Hadley Wickham, having just taught workshops in DC for RStudio, shared with the DC R Meetup his view on the future, or at least the near future of Data Analysis. … Continue reading → The post The (near) Future of Data Analysis – A Review appeared first on...

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The Unravelling of Structured Investment Vehicles or Birthdays

January 2, 2013
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The best way for me to achieve deep understanding of a theorem is not through lengthy proofs alone, but through practical application/implementation or as they said in the Marine Corps Pract-App. One of the many reasons I love R is the ease to write functions and test results. The 2008 financial crisis was the topic of a recent dinner

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You can’t spell loss reserving without R

January 2, 2013
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You can’t spell loss reserving without R

Last year, I spent a morning trying to return to first principles when modeling loss reserves. (Brief aside to non-actuaries: a loss reserve is the financial provision set aside to pay for claims which have either not yet settled, or have not yet been reported. If that doesn’t sound fascinating, this will likely be a

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Computing for Data Analysis, and Other Free Courses

January 2, 2013
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Coursera's free Computing for Data Analysis course starts today. It's a four week long course, requiring about 3-5 hours/week. A bit about the course:In this course you will learn how to program in R and how to use R for effective data analysis. Y...

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R code and data for book “R and Data Mining: Examples and Case Studies”

January 2, 2013
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R code and data for book “R and Data Mining: Examples and Case Studies”

R code and data for book “R and Data Mining: Examples and Case Studies” are now available at http://www.rdatamining.com/books/rdm/code. An online PDF version of the book (the first 11  chapters only) can also be downloaded at http://www.rdatamining.com/docs. Below are its … Continue reading →

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NFL Code on Github

January 2, 2013
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NFL Code on Github

I’ve made some revisions and simplifications to the code to compile NFL data. It’s now all out on Github for anyone to play with in advance of the Superbowl. In the meantime, here’s a lovely picture comparing every team’s offense- as measured by total offensive yards- against their defenders. Note the anemic Chicago offense. https://github.com/PirateGrunt/NFL

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