Monthly Archives: February 2013

Why cost and fuel efficiency are unrelated: Uncorrelated manifest variables can share the same latent causes

February 7, 2013
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Why cost and fuel efficiency are unrelated: Uncorrelated manifest variables can share the same latent causes

In structural equation modelling, we are typically proposing theoretical causes of observed phenomena. These are termed "latent" (the unobserved causes) and manifest (the observed variables we measure, otherwise known as data).Importantly, the theoretical causes of behavior need not have a structure remotely resembling the correlations observed in the data. You might have hundreds of columns of...

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Using ARPACK to compute the largest eigenvalue of a matrix

February 7, 2013
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Thanks to Gábor Csárdi, author of the R interface to ARPACK, for this example of using (the R/Igraph interface to) arpack for finding the largest eigenvalue of a matrix. The key insight is that arpack solves the function passed to … Continue reading →

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Creating ‘Tags’ For PPC Keywords

February 7, 2013
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Creating ‘Tags’ For PPC Keywords

When performing search engine marketing, it is usually beneficial to construct a system for making sense of keywords and their performance. While one could construct Bayesian Belief Networks to model the process of consumers clicking on ads, I have found that using ’tags’ to categorize keywords is just as useful for conducting post-hoc analysis on the effectiveness of marketing

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Data analysis class

February 7, 2013
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Data analysis class

I've been writing software to help others do data analysis for a number of years and at the same time trying to work up my nerve to try my own analysis. Why let other people have all the fun? So, when I saw that Jeffrey Leek, biostatistician at Johns Hopkins and coauthor of Simply Statistics, was teaching...

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R Bootcamp @ Sector67 in Madison

February 6, 2013
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I am pleased to announce that together with Justin Meyer (also from the Wisconsin Department of Public Instruction) I will be presenting a two hour version of the R Bootcamp. Sector67 is a collaborative maker/hacker space in Madison, and is a great ven...

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Ryan Peek on using xts and ggplot for time-series data

February 6, 2013
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Ryan Peek on using xts and ggplot for time-series data

At Davis R Users’ Group today, Ryan Peek gave a presentation on how he takes data from his field instruments and visualizes it in R. Here are his notes. The original *.Rmd file and data can be found here SHORT HOW-TO ON USING XTS AND GGPLOT FOR TIME SERIES DATA XTS is a very helpful package...

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Set operations on more than two sets in R

February 6, 2013
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ProblemSet operations are a common place thing to do in R, and the enabling functions in the base stats package are:intersect(x, y)union(x, y)setdiff(x, y)setequal(x, y)That said, you'll note that each ONLY takes two arguments - i.e. set X and set Y - ...

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Modelling memory and news trajectories

February 6, 2013
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Modelling memory and news trajectories

Modelling memory In the text below I present two models I've made to quantify and visualise the diverging trajectories of memory and news events, and conclude that linear regression may be used to test which model best describes the story. First, though, I contextualise this with an illustration from the...

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Oracle R Enterprise 1.3 gives predictive analytics an in-database performance boost

February 6, 2013
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Oracle R Enterprise 1.3 gives predictive analytics an in-database performance boost

Recently released Oracle R Enterprise 1.3 adds packages to R that enable even more in-database analytics. These packages provide horizontal, commonly used techniques that are blazingly fast in-database for large data. With Oracle R Enterprise 1.3, Oracle makes R even better and usable in enterprise settings. (You can download ORE 1.3 here and documentation here.) ...

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Make building R packages easier with devtools

February 6, 2013
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If you're writing any significant amount of R code, you might want to start think about bundling it up into packages. An R package combines functions, data, documentation and unit tests, and is a convenient and reliable system to manage and version collections of R content that could otherwise become unwieldy. And if you want to share your code...

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