Monthly Archives: November 2010

Stat Computing Visions from the Past

November 18, 2010
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Stat Computing Visions from the Past

I recently stumbled upon an old paper of a presentation I gave at the Interface conference in 1998, entitled “JAVA – the next Generation of Statistical Computing?”: It is very interesting to compare the things I envisioned 12 years ago and what actually came true. Here are some topics: Did Java change a whole lot

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Logistic regression – simulation for a power calculation…

November 18, 2010
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Logistic regression – simulation for a power calculation…

Please note - I’ve spotted a problem with the approach taken in this post – it seems to underestimate power in certain circumstances. I’ll post again with a correction or a more full explanation when I’ve sorted it. So, I posted an answer on cross validation regarding logistic regression.   I thought I’d post it

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dcemriS4 0.40

November 18, 2010
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dcemriS4 0.40

The R package dcemriS4 is a collection of functions, with examples and documentation, that allows one to perform voxel-wise quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) or diffusion-weighted imaging (DWI) data.  The primary...

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Introducing Monte Carlo in PaRis [more slides]

November 17, 2010
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Introducing Monte Carlo in PaRis [more slides]

The class started yesterday with a small but focussed and responsive audience! Given the background of the students, and in particular their clear proficiency in R!, I switched between the original slides of Introducing Monte Carlo Methods with R and those of my Monte Carlo Statistical Methods: course, updated by Olivier Cappé who is teaching

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Wanted: R hackers for Revolution

November 17, 2010
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Revolution Analytics is growing, and we're looking for some skilled R Hackers to work in our pre-Sales team. A big part of our task is showing companies how R is such a great tool for modern data analysis (especially compared to those older tools with 3- or 4-letter acronyms). So if you have a knack for applying R to...

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Its 9am, do you know what the traders are thinking?

November 17, 2010
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Its 9am, do you know what the traders are thinking?

Roll proposed a model for the bid-ask spread that was based on first-order serial correlation.  His empirical tests were based on daily and weekly frequency equity data, and based on the results he concluded there were informational inefficiencies (or that there was very short term non-stationarity in expected returns).More recently this model has been applied to high...

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Syntax Highlighting R Code, Revisited

November 17, 2010
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A few months ago I showed you how to syntax-highlight R code using Github Gists for displaying R code on your blog or other online medium. The idea's really simple if you use blogger - head over to gist.github.com, paste in your R code, create a public "gist", hit "embed", then copy the javascript onto your blog. However, if...

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Updated SoilWeb Usage Statistics

November 16, 2010
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Updated SoilWeb Usage Statistics

Google Earth Access Trends: Daily Requests read more

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ACM Data Mining Camp

November 16, 2010
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ACM Data Mining Camp

By guest blogger Joseph Rickert. I was very happy to be a part of the ACM Data Mining camp held last Saturday (November 13th) at eBay. It was a big day for discussing hot topics in data mining, Mahout, parallel SVMs etc, and also a pretty big day for R. Because Revolution Analytics was a sponsor for the camp,...

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Visualizing US House Results with a Seats-Votes curve

November 16, 2010
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Visualizing US House Results with a Seats-Votes curve

A few weeks ago I wrote about ways to compare major-party returns in US House elections. I experimented with several visualizations, none as useful as the seats-votes curve. A traditional seats-votes cure measures average party performance against individual US House results. Our simplified curve uses a density plot to measure major-party (Democratic, in this case)

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