Publications by Joseph Rickert
R User Groups June 2014
by Joseph Rickert useR! 2014 is just about two weeks away, and I am very much looking forward to meeting R users from around the world. This is just a great time to catch up with old friends, hopefully make some new friends, and talk about R and R user groups. The number of R user groups continues to increase. Over the past six months, new grou...
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Constructing a Continuous Futures Series From Quandl
by Ilya Kipnis In this post, I will demonstrate how to obtain, stitch together, and clean data for backtesting using futures data from Quandl. Quandl was previously introduced in the Revolutions Blog. Functions I will be using can be found in my IK Trading package available on my github page. With backtesting, it’s often times easy to get da...
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Contest: Prizes for Best R User Groups Plotting Code
by Joseph Rickert For the past year or so we have been plotting the location of R user groups around the world using code (Download RUGS) adapted from a solution that Sandy Muspratt originally posted on Stack Overflow. In last week’s post, we made a modest improvement to our presentation by including a map of Europe. However, R users are doing...
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Statistics and R at the Intel ISEF Science Fair
by Wayne Smith, Ph.D. California State University, Northridge Editor's note: This post was abstracted from the monthly newsletter of the Southern California Chapter of the ASA. On May 13th and 14th, the Intel International Science and Engineering Fair (Intel ISEF) the world’s largest international pre-college competition, was held at the Los An...
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Review of Applied Predictive Modeling by Kuhn and Johnson
by Joseph Rickert Predictive Modeling or “Predictive Analytics”, the term that appears to be gaining traction in the business world, is driving the new “Big Data” information economy. Predictably, there is no shortage of material to be found on this subject. Some discussion of predictive modeling is sure to be found in any reasonably tech...
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Quantitative Finance applications in R – 7: Constructing a Term Structure of Interest Rates Using R (part 2 of 2)
by Daniel Hanson Recap and Introduction Last time in part 1 of this topic, we used the xts and lubridate packages to interpolate a zero rate for every date over the span of 30 years of market yield curve data. In this article, we will look at how we can implement the two essential functions of a term structure: the forward interest rate, and ...
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UseR! 2014 Tutorials
by Joseph Rickert UserR! 2014 got under way this past Monday with a very impressive array of tutorials delivered on the day that the conferences organizers were struggling to cope with a record breaking crowd. My guess is that conference attendance is somewhere in the 700 range. Moreover, this the first year that I can remember that tutorials wer...
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Reflections on John Chambers’ UserR! 2014 Keynote Address
by Joseph Rickert John Chambers opened UseR! 2014 by describing how the R language grew out of early efforts to give statisticians easier access to high quality statistical software. In 1976 computational statistics was a very active field, but most algorithms were compiled as Fortran subroutines. Building models with this software was not a triv...
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Preparing Big Data for Analysis in R
by Yaniv Mor, Co-founder & CEO of Xplenty How do you get Big Data ready for R? Gigabytes or terabytes of raw data may need to be combined, cleaned, and aggregated before they can be analyzed. Processing such large amounts of data used to require installing Hadoop on a cluster of servers, not to mention coding MapReduce jobs in Pig or Java. Those ...
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R and Meta-Analysis
by Joseph Rickert Broadly speaking, a meta-analysis is any statistical analysis that attempts to combine the results of several individual studies. The term was apparently coined by statistician Gene V Glass in a 1976 speech he made to the American Education Research Association. Since that time, not only has meta-analysis become a fundamental ...
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