Monthly Archives: March 2013

Open Data Exchange 2013, April 6. Montreal

March 29, 2013
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Open Data Exchange 2013, April 6. Montreal

UPDATE: The day was great! There are many people doing really amazing things with open data and it was amazing to meet them. Here are my slides from the panel talk. Next Saturday, I’ll be sitting on a panel discussing future avenues for open data at ODX13. From the odx13 site: Odx13 is a mini-conference

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latent Gaussian model workshop in Reykjavik

March 28, 2013
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latent Gaussian model workshop in Reykjavik

An announcement for an Icelandic meeting next September, meeting I would have loved to attend (darn!)… This meeting is sponsored by the BayesComp session, of course!!! We are pleased to announce that the University of Iceland will host the 3rd Workshop on Bayesian Inference for Latent Gaussian Models with Applications (LGM). The workshop will be

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The apply function in R

March 28, 2013
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So as discussed in this post I will be investigating the different members of the 'apply function family' in R. This post starts with the most basic one, called apply(). The R manual states the following apply(X, MARGIN, FUN, ...) With the following arguments X an array, including a matrix. MARGIN a vector giving the subscripts which

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Moving up in the ranks: from an R-Rookie to an R-Pro

March 28, 2013
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I am playing with R now for little over a year. Not very intensive, but once in a while I start up R Studio and do some coding and analysis. But I am still far, far away from becoming an R-Pro. If you talk to or read some of the posts of the more seaso...

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Swimming in a sea of code

March 28, 2013
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Swimming in a sea of code

If you are looking for code here, move on. > In the beginning, there was only the relentless blinking of the cursor. With the maddening regularity of waves splashing on the shore: blink, blink, blink, blink…Beyond the cursor, the white wasteland … Continue reading →

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Playing with earthquake data

March 28, 2013
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(This article was first published on Digithead's Lab Notebook, and kindly contributed to R-bloggers) To leave a comment for the author, please follow the link and comment on his blog: Digithead's Lab Notebook. R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git,...

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Creating a Business Dashboard in R

March 28, 2013
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Creating a Business Dashboard in R

Business dashboards are available in many shapes and sizes. Business dashboards are useful to create an overview of key performance indicators (KPIs) important for the business strategy and/or operations. There are many flavours of dashboard frameworks and apps available, ranging in price from thousands of dollars to open-source implementations. Apparently  Read more »

Data visualization with R and ggplot2

March 28, 2013
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Data visualization with R and ggplot2

I’m working on a one-hour ggplot2 lecture for the San Diego R users group, which I will post here when I’m done. I think there are many great intro to R data visualization resources out there so I’ll only share working examples on my blog. A retail chain client employs a few hundred field agents who perform

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Generalized Pairs Plot: It’s about time!

March 28, 2013
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Generalized Pairs Plot: It’s about time!

JW Emerson, WA Green, B Schloerke, J Crowley, D Cook, H Hofmann, H Wickham (2013) The Generalized Pairs Plot. Journal of Computational and Graphical Statistics 22(1). Here's a free preprint version. Until this new paper and implementation by Emerson et al., there were no widely available pairs plots that accommodated both numerical and categorical fields.

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Benford law and lognormal distributions

March 28, 2013
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Benford law and lognormal distributions

Benford’s law is nowadays extremely popular (see e.g. http://en.wikipedia.org/…). It is usually claimed that, for a given set data set, changing units does not affect the distribution of the first digit. Thus, it should be related to scale invariant distributions. Heuristically, scale (or unit) invariance means that the density of the measure  (or probability function) should be proportional to...

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