Slides for Revolution R Enterprise: 100% R and more

October 20, 2011
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If you haven't yet taken a look at Revolution R Enterprise but wanted to know what is adds to open-source R, the slides below from yesterday's webinar will give you a quick overview: A recorded replay with audio of the me giving the presentation is also available at the link below. Revolution Analytics Webinars: Revolution R Enterprise: 100% R...

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Spatial correlation in designed experiments

October 20, 2011
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Spatial correlation in designed experiments

Last Wednesday I had a meeting with the folks of the New Zealand Drylands Forest Initiative in Blenheim. In addition to sitting in a conference room and having nice sandwiches we went to visit one of our progeny trials at … Continue reading →

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Shipping Mix

October 20, 2011
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Shipping Mix

With a fresh pile of historical global shipping data, we came back to the flow visualizations that illustrated tangible supply lines that facilitate global trade.  This time we've isolated two types of shipping vessels, cargo and tanker, in order ...

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Queueing up in R, continued

October 20, 2011
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Queueing up in R, continued

Shown above is a queueing simulation. Each diamond represents a person. The vertical line up is the queue; at the bottom are 5 slots where the people are attended. The size of each diamond is proportional to the log of the time it will take them to be attended. Color is used to tell one

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postdoctoral positions in Paris

October 20, 2011
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postdoctoral positions in Paris

There is a call for postdoctoral positions supported by the Paris Mathematical Sciences Foundation. The deadline is December 13 and the on-line application is available. If you are interested in working with me on Bayesian statistics  (model choice, time series model) or computational methods (SMC, MCMC, ABC, &c.) thru this call, please contact me at

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Does the S&P 500 exhibit seasonality through the year?

October 20, 2011
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Does the S&P 500 exhibit seasonality through the year?

Are there times of the year when returns are better or worse? Abnormal Returns prompted this question with “SAD and the Halloween indicator” in which it is claimed that the US market tends to outperform from about Halloween until April. Data The data consisted of 15,548 daily returns of the S&P 500 starting in 1950.  … Continue reading...

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Confidence interval diagram in R

October 19, 2011
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Confidence interval diagram in R

This code shows how to easily plot a beautiful confidence interval diagram in R. First, let’s input the raw data. We’ll be making two confidence intervals for two samples of 10. In case you curious, the data represents samples from … Continue reading →

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R. I. P. EMA

October 19, 2011
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R. I. P. EMA

That’s right, I am moving away from exponential moving averages. Originally, I decided to use them somewhat arbitrary, probably because they tend to swing faster. Last night, after spending two and half hours debugging an issue which yet again turned out to be a particular property of these averages, I made my mind. I am

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Minimum Investment and Number of Assets Portfolio Cardinality Constraints

October 19, 2011
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Minimum Investment and Number of Assets Portfolio Cardinality Constraints

The Minimum Investment and Number of Assets Portfolio Cardinality Constraints are practical constraints that are not easily incorporated in the standard mean-variance optimization framework. To help us impose these real life constraints, I will introduce extra binary variables and will use mixed binary linear and quadratic programming solvers. Let’s continue with our discussion from Introduction

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the Wang-Landau algorithm reaches the flat histogram in finite time

October 19, 2011
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the Wang-Landau algorithm reaches the flat histogram in finite time

Pierre Jacob and Robin Ryder (from Paris-Dauphine, CREST, and Statisfaction) have just arXived (and submitted to the Annals of Applied Probability) a neat result on the Wang-Landau algorithm. (This algorithm, which modifies the target in a sort of reweighted partioned sampling to achieve faster convergence, has always been perplexing to me.)  They show that some

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Support Vector Machines in R (a course by Lutz Hamel)

October 19, 2011
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Support vector machines (SVM’s) are the “big iron” of the data mining world, especially suited for extreme data intensive tasks like image classification, biosequence processing, handwriting recognition, etc. Dr. Lutz Hamel, author of “Knowledge Discovery with Support Vector Machines”, presents his online course “Introduction to Support Vector Machines In R” November 18 – December 16. “Support Vector Machines in...

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Web-friendly visualizations in R

October 19, 2011
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Aleks points me to this new tool from Wojciech Gryc. Right now I save my graphs as pdfs or pngs and then upload them to put them on the web. I expect I’ll still be doing this for awhile—I like having full control of what my graphs look like—but Gryc’s default plots might be useful The post Web-friendly...

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On R, bloggers, politics, sex, alcohol and rock & roll

October 19, 2011
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On R, bloggers, politics, sex, alcohol and rock & roll

Yesterday morning at 7 am I was outside walking the dog before getting a taxi to go to the airport to catch a plane to travel from Christchurch to Blenheim (now I can breath after reading without a pause). It … Continue reading →

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The R-Files: Paul Teetor

October 19, 2011
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The R-Files: Paul Teetor

"The R-Files" is an occasional series from Revolution Analytics, where we profile prominent members of the R Community. Name: Paul Teetor Profession: Quantitative developer (freelance) Nationality: American Years Using R: 7 Known for: Author of R Cookbook (O’Reilly Media, 2011) An active member of the R community, Paul Teetor is a quantitative developer and statistical consultant based in the...

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Studying market reactions after consecutive gains (losses)

October 19, 2011
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Studying market reactions after consecutive gains (losses)

Arthur Charpentier used R to denote a broken record of the CAC 40 when it went 11 consecutive days with negative returns. Question: What happens to the market after runs of positive or negative returns? Will the market tank or soar after n days of gains/losses? First, a little dissection of historical data (S&P 500

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How does Matt kemp become Andre Dawson?

October 18, 2011
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How does Matt kemp become Andre Dawson?

While reading this article over at Fangraphs I was inspired to ask myself “what would Matt Kemp have to do between now and then end of his career to be seriously considered for the Hall of Fame?”.  This question comes … Continue reading →

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Fusion Tables by Google

October 18, 2011
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Google's Fusion Tables look impressive, for those who want to try geo-visualizations of their data. You don't need much programming experience to be able to use it.For those who want to try it out, here's a nice intro that Kathyrn Hurley presented at the recent SVCC (Silicon Valley Code Camp). When combined with ShpEscape (note spelling) it becomes...

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Generating restricted permutations with permute

October 18, 2011
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Generating restricted permutations with permute

In a previous post I introduced the permute package and the function shuffle(). In that post I got as far as replicating R’s base function sample(). Here I’ll briefly outline how shuffle() can be used to generate restricted permutations. shuffle() … Continue reading →

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130/30 Porfolio Construction

October 18, 2011
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130/30 Porfolio Construction

The 130/30 funds were getting lots of attention a few years ago. The 130/30 fund is a long/short portfolio that for each $100 dollars invested allocates $130 dollars to longs and $30 dollars to shorts. From portfolio construction perspective this simple idea is no so simple to implement. Let’s continue with our discussion from Introduction

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Large applications of linear mixed models

October 18, 2011
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Large applications of linear mixed models

In a previous post I summarily described our options for (generalized to varying degrees) linear mixed models from a frequentist point of view: nlme, lme4 and ASReml-R†, followed by a quick example for a split-plot experiment. But who is really … Continue reading →

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ACM Data Mining Camp 2011: Report

October 18, 2011
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(By Joseph Rickert.) In San Jose topics like big data, map reduce, predictive models, mobile analytics and crowdsourcing draw a crowd even on a Saturday. So it turned out that the ACM data Mining Camp and "un-conference" was a very "happening" way to spend a Saturday. Over 500 people attended the event at the Ebay "Town Hall" on North...

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Generating restricted permutations with permute

October 18, 2011
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In a previous post I introduced the permute package and the function shuffle(). In that post I got as far as replicating R’s base function sample(). Here I’ll briefly outline how shuffle() can be used to generate restricted permutations.

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Short selling, volatility and bubbles

October 17, 2011
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Short selling, volatility and bubbles

Yesterday, I wrote a post (in French) about short-selling in financial market since some journalists claimed that it was well-known that short -selling does increase volatility on financial market. Not only in French speaking journals actually, sin...

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Get the Basics right – Suggestion for R Beginners

October 17, 2011
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I am always looking for suggestions on how to get better at R, esp. for beginners. So when I see someone who's gotten adept at it, I ask them how they got there.This weekend, at the Bay Area ACM Data Mining Camp, one person gave me what seemed like a g...

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Revolution Newsletter: October 2011

October 17, 2011
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The most recent edition of the Revolution Newsletter is out. The news section is below, and you can read the full October edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. Applications of R Contest: Deadline October 31. Revolution Analytics is offering $20,000 in prizes...

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R Tools for FEC Campaign Finance Disclosure Data

October 17, 2011
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R Tools for FEC Campaign Finance Disclosure Data

For my first contribution to the blog, I wanted to make some kind of enlightening visualization of campaign finance disclosure data from the Federal Election Commission’s website. It looks like they’re working on some new, easy-to-use data dumps here, but … Continue reading →

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Lattice when modeling, ggplot when publishing

October 17, 2011
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Lattice when modeling, ggplot when publishing

When working in research projects I tend to fit several, sometimes quite a few, alternative models. This model fitting is informed by theoretical considerations (e.g. quantitative genetics, experimental design we used, our understanding of the process under study, etc.) but … Continue reading →

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Software for Research, Part 3: [R], RStudio and ggplot2 for Statistics

October 17, 2011
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Software for Research, Part 3: [R], RStudio and ggplot2 for Statistics

is an excellent open-source statistics language. It's cross-platform and free and I think it will eventually displace proprietary stat's packages due to its rapid development, speed and ease of use. So there's no time like the present to get used...

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Colors in R

October 17, 2011
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Colors in R

One of my favorite R packages that I use all the time is the RColorBrewer package. The package has been around for a while now and is written/maintained by Erich Neuwirth. The guts of the package are based on Cynthia Brewer’s very cool work on the us...

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