Blog Archives

Reflections on John Chambers’ UserR! 2014 Keynote Address

July 10, 2014
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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 trivial process. First you had...

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UseR! 2014 Tutorials

July 3, 2014
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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 were...

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Quantitative Finance applications in R – 7: Constructing a Term Structure of Interest Rates Using R (part 2 of 2)

July 1, 2014
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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:...

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Review of Applied Predictive Modeling by Kuhn and Johnson

June 26, 2014
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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 technical presentation of business decision...

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Statistics and R at the Intel ISEF Science Fair

June 24, 2014
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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 Angeles Convention Center. I was blessed with the...

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Contest: Prizes for Best R User Groups Plotting Code

June 19, 2014
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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...

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Constructing a Continuous Futures Series From Quandl

June 17, 2014
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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 data...

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R User Groups June 2014

June 12, 2014
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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...

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Quantitative Finance Applications in R – 6: Constructing a Term Structure of Interest Rates Using R (Part 1)

June 10, 2014
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Quantitative Finance Applications in R – 6:   Constructing a Term Structure of Interest Rates Using R (Part 1)

by Daniel Hanson Introduction Last time, we used the discretization of a Brownian Motion process with a Monte Carlo method to simulate the returns of a single security, with the (rather strong) assumption of a fixed drift term and fixed volatility. We will return to this topic in a future article, as it relates to basic option pricing methods,...

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Deep Learning at Stanford

June 5, 2014
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Deep Learning at Stanford

by Joseph Rickert Last week,I had the opportunity to participate in the Second Academy of Science and Engineering (ASE) Conference on Big Data Science and Computing at Stanford University. Since the conference was held simultaneously with the two other conferences, one on Social Computing and the other on Cyber Security, it was definitely not an R crowd, and not...

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