Monthly Archives: June 2013

My R package’s worldmap of downloads!

June 18, 2013
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My R package’s worldmap of downloads!

Last week, a colleague draw my attention on this new log files from the Rstudio cloud CRAN mirror, through a post from Tal Galili. This CRAN mirror is a little different, as it uses Amazon CloudFront to deliver the downloads … Continue reading →

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The Fallacy of 1/N and Static Weight Allocation

June 18, 2013
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The Fallacy of 1/N and Static Weight Allocation

In the last few years there has been a increasing tendency to ignore the value of a disciplined quantitative approach to the portfolio allocation process in favor of simple and static weighting schemes such as equal weighting or some type of adjusted volatility weighting. The former simply ignores the underlying security dynamics, assuming equal risk-return,

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The Fallacy of 1/N and Static Weight Allocation

June 18, 2013
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The Fallacy of 1/N and Static Weight Allocation

In the last few years there has been a increasing tendency to ignore the value of a disciplined quantitative approach to the portfolio allocation process in favor of simple and static weighting schemes such as equal weighting or some type of adjusted volatility weighting. The former simply ignores the underlying security dynamics, assuming equal risk-return,

Read more »

Create SAS Code from R ‘tree’ Objects

June 18, 2013
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Create SAS Code from R ‘tree’ Objects

I recently was faced with the desire to port some tree models developed in R to SAS so I could score a large database. To me this makes sense as SAS is better with large files (or at least so as not to offend anyone, I am better with large files in SAS). I started

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Printing R help files in the console or in knitr documents

June 18, 2013
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Yesterday, I was creating a knitr document based on a script, and was looking for a way to include content from an R help file. The script, which was a teaching document, had a help() command for when the author wanted to refer readers to R documentation. I wanted that text in my final document, though. There’s no...

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Resources for getting started with R

June 18, 2013
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Resources for getting started with R

As we believe you may know, we are having a webinar tomorrow (June 19th, 2013) on Predictive Analytics. During this webinar, you are going to be introduced to R, learn how to build a predictive model and also how to carry insightful analysis through visualization. As learning a new language can be a really difficult

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BCEA 1.3.0

June 18, 2013
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BCEA 1.3.0

After months of work (although to be fair, we haven't worked 100% full time on this), Andrea and I are nearly ready to publish the next release of BCEA. Andrea has done a brilliant job and is responsible for most of the good new features (NB: see ...

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PivotalR Improves the Scalability and Performance of In-Database Analytics

June 18, 2013
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PivotalR Improves the Scalability and Performance of In-Database Analytics

One of the greatest challenges while working with big datasets concerns the need to move information out of storage for analysis. To this end, the recent announcement of PivotalR 0.1 extends Pivotal HD's capabilities, allowing users of the statistical programming language R to perform in-database analytics without leaving the command line.

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R GIS: Terrain Analysis for Polygons as Simple as it Gets!

June 18, 2013
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R GIS: Terrain Analysis for Polygons as Simple as it Gets!

library(rgdal)library(raster)alt gadm gadm_sub plot(alt)plot(gadm_sub, add=T)asp slo > extract(slo, gadm_sub, fun = mean, na.rm = T, small = T, df = T) ID slope1 1 9.9590532 2 1.0474433 3 7.4561654 4 1.6737865 5 11.946553> extract(asp, gadm_sub, fun = mean, na.rm = T, small...

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The Green Number Effect

June 18, 2013
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The Green Number Effect

Following up on a suggestion from my previous post, here are the statistics for medal count versus age. Every point on the plot is the number (see colour legend on right) of athletes who have achieved a given number of medals by a particular age. There is clear evidence of a Green Number Effect: many

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