Monthly Archives: April 2013

A nifty line plot to visualize multivariate time series

April 1, 2013
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A nifty line plot to visualize multivariate time series

A few days ago a colleague came to me for advice on the interpretation of some data. The dataset was large and included measurements for twenty-six species at several site-year-plot combinations. A substantial amount of effort had clearly been made to ensure every species at every site over several years was documented. I don’t pretend

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Updating R (on Windows) through a menu-bar: installr 0.9 released on CRAN

April 1, 2013
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Updating R (on Windows) through a menu-bar: installr 0.9 released on CRAN

In preparation for the upcoming release of R 3.0.0, a new release 0.9 of installr is now on CRAN. The package can be installed and loaded using: # installing/loading the package: if(!require(installr)) { install.packages("installr"); require(installr)} #load / install+load installr The …Read more »

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R Tackles Big Garbage

April 1, 2013
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R Tackles Big Garbage

April 1, 2013 – Although the capabilities of the R system for data analytics have been expanding with impressive speed, it has heretofore been missing important fundamental methods. A new function works with the popular plyr package to provide these missing … Continue reading →

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A pictorial history of US large cap correlation

April 1, 2013
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A pictorial history of US large cap correlation

How has the distribution of correlations changed over the last several years? Previously Posts about correlation boxplots explained Data Daily returns of 443 large cap US stocks from 2004 through 2012 were used.  The sample correlations — almost 98,000 of them — during each year were created. If we were actually using the correlations, then … Continue reading...

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The R-Podcast Episode 12: Using Version Control with R

April 1, 2013
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This is not an April Fool’s joke … The R-Podcast is back once again! In this episode, I discuss the concept of version control and how you can get started with using the Git VCS right now with your R projects. Also I discuss a big batch of listener feedback, and highlight a couple of

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