Monthly Archives: December 2010

R 2.12.1 scheduled for December 16

December 6, 2010
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The next update to R will be a patch release: R 2.12.1 will be released on December 16, as announced today by the R Core Team. As is typical for a patch release, this version will include some minor bug fixes plus a few new features (from the current build's NEWS file): The DVI/PDF reference manual now includes the...

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Jeromy Anglim on Reproducible Research and R

December 6, 2010
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Jeromy Anglim, fellow social scientist and R aficionado from across the globe, gave a great talk to the Melbourne R Users Group last week on the joys of creating reproducible results. A subject near and dear to me, but not one that is given enough attention in research training. Jeromy discusses tools for generating reproducible

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What my R code looks and feels like (Vanilla)

December 6, 2010
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Geoff Robinson discusses how to write simple and reusable R code. He provides several examples with code.

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Reproducible Research and R Workflow

December 6, 2010
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Jeromy Anglim discusses best practices and tools used to support reproducible research in R. He discusses tools for R scripting and version control; and provides examples of SWeave. This presentation was given to the Melbourne R Users Group (MelbURN)...

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3 weak days in a row

December 6, 2010
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3 weak days in a row

Recently, Trading the odds posted one of many flavors of mean reverting strategies and I decided to get my hands dirty by writing R code and testing it. You can find full description of the strategy by following latter link above. Long story short – if SPY shows lower open, high and close 3 days in

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JAGS – Bayesian Analysis

December 6, 2010
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JAGS – Bayesian Analysis

JAGS is used for Bayesian analysis using MCMC and stands for Just Another Gibbs Sampler.  It is an alternative to WinBUGS and can be accessed through R just like WinBUGS (via R2jags or RJags).  It will work on a Mac unlike WinBUGS.  The ...

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Using the "Divide by 4 Rule" to Interpret Logistic Regression Coefficients

December 6, 2010
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I was recently reading a bit about logistic regression in a book on hierarchical/multilevel modeling when I first learned about the "divide by 4 rule" for quickly interpreting coefficients in a logistic regression model in terms of the predicted probabilities of the outcome. The idea is pretty simple. The logistic curve (predicted probabilities) is steepest at the center where...

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Example 8.17: Logistic regression via MCMC

December 6, 2010
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Example 8.17: Logistic regression via MCMC

In examples 8.15 and 8.16 we considered Firth logistic regression and exact logistic regression as ways around the problem of separation, often encountered in logistic regression. (Re-cap: Separation happens when all the observations in a category sha...

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Electoral Marimekko Plots

December 6, 2010
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Electoral Marimekko Plots

To be reductive, visual displays of quantitative information might be reasonably categorized on a continuum between “data display” and “statistical graphics.” By statistical graphics, I mean a plot that displays some summary of or relationship amongst several variables, likely having undergone some processing or analysis. This may be as simple as a scatterplot of a … Continue reading →

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Bear hunting

December 6, 2010
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Bear hunting

When were there bear and bull markets in US stocks since 1950? Smoothing While we’d really like to estimate the expected return at each point in time, finding bear markets is ambitious enough.  The plan starts by smoothing the daily returns through time, as in Figure 1. Figure 1: Smoothed returns with a 4 year … Continue reading...

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