Monthly Archives: October 2012

A Greedy ARMA/GARCH Model Selection

October 26, 2012
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An idea that I have been toying for a while, has been to study the effect of a domain-specific optimization strategy in the ARMA+GARCH models. If you recall from this long tutorial, the implemented approach cycles through all models within a the specified ranges for the parameters and chooses the best model based on the

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R 2.15.2 now available

October 26, 2012
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As promised, the source distribution for R 2.15.2 is now available for download from the master CRAN repository. (Binary distributions for Windows, MacOS and Linux will be available from the CRAN mirror network in the coming days.) This latest point-update — codenamed "Trick or Treat" — improves the performance of the R engine and adds a few minor but...

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Chris Hamm on using plot.new() for better combined plots

October 26, 2012
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Chris Hamm on using plot.new() for better combined plots

At DRUG today, Chris Hamm (email (cahamm at ucdavis dot edu)) showed us an easier way to combine multiple figures into one plot using plot.new, rather than par(mfrow=...) Here’s his script: A Report Generated by knitr # plot.new() [email protected] #I discovered this plotting method when trying to add an inset figure # to a plot # plot.new is part of the traditional graphics....

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Javascript and D3 for R users, part 2: running off the R server instead of Python

October 26, 2012
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Thank you all for the positive responses to Basics of JavaScript and D3 for R Users! Quick update: last time we had to dabble in a tiny bit of Python to start a local server, in order to actually run JavaScript … Continue reading →

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Plotting correlation ellipses

October 26, 2012
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Plotting correlation ellipses

This is an oldie but a goodie. There are a lot of ways to plot multiple bivariate relationships, but this is one of my favorites, courtesy of the R Graph Gallery. https://gist.github.com/819111

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NSCB Sexy Stats Version 2

October 25, 2012
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NSCB Sexy Stats Version 2

This was a revised version of my previous post about the NSCB article. With the suggestion from Tal Galili, below were the new pie charts and the R codes to produce these plots by directly scrapping the data from the webpage using XML and RColorBrewer ...

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Using FAFSA Data to study Competitors – Part 2

October 25, 2012
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Using FAFSA Data to study Competitors – Part 2

I wanted to build upon my previous post and dive a little deeper into the sorts of questions we can answer using the FAFSA data supplied to us by applicants. As a quick overview, students completing the FAFSA for student aid can list up to ten institutions on the form. I consider this the student’s

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Modeling Couch Potato strategy

October 25, 2012
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Modeling Couch Potato strategy

I first read about the Couch Potato strategy in the MoneySense magazine. I liked this simple strategy because it was easy to understand and easy to manage. The Couch Potato strategy is similar to the Permanent Portfolio strategy that I have analyzed previously. The Couch Potato strategy invests money in the given proportions among different

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Accelerating R code: Computing Implied Volatilities Orders of Magnitude Faster

October 25, 2012
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This blog, together with Romain's, is one of the main homes of stories about how Rcpp can help with getting code to run faster in the context of the R system for statistical programming and analysis. By making it easier to get already existing C or C++ code to R, or equally to extend R with new C++...

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My Goodness. What a Fat Dataset!

October 25, 2012
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My Goodness.  What a Fat Dataset!

Recently at work we got sent a data file containing information on donations to a specific charitable organization, ranging all the way back to the 80′s.  Usually, when we receive a dataset with a donation history in it, each row … Continue reading →

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