Monthly Archives: October 2012

Feature selection and linear modeling

October 27, 2012
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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 their blog: Digithead's Lab Notebook. R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming...

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.Rhistory

October 27, 2012
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Over the last couple of years I've been using R every now and then. When I stumbled upon an interesting topic, and I managed to get a hold of a data set, I tried to make sense of it using R.It's a bit like the Stat Labs approach: I might get started by...

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Book Review: R for Business Analytics, A Ohri

October 26, 2012
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Book Review:    R for Business Analytics,    A Ohri

      I've added a recently released book to my list of recommendations (at the amazon carousel to the right), as I've reviewed a copy provided to me via Springer Publishers. The book is R for Business Analytics, authored by A Ohri.&nbsp...

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A Greedy ARMA/GARCH Model Selection

October 26, 2012
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An idea that I have been toying for a while, has been to study the effect of a domain-specific optimization strategy in the ARMA+GARCH models. If you recall from this long tutorial, the implemented approach cycles through all models within a the specified ranges for the parameters and chooses the best model based on the

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R 2.15.2 now available

October 26, 2012
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As promised, the source distribution for R 2.15.2 is now available for download from the master CRAN repository. (Binary distributions for Windows, MacOS and Linux will be available from the CRAN mirror network in the coming days.) This latest point-update — codenamed "Trick or Treat" — improves the performance of the R engine and adds a few minor but...

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Chris Hamm on using plot.new() for better combined plots

October 26, 2012
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Chris Hamm on using plot.new() for better combined plots

At DRUG today, Chris Hamm (email (cahamm at ucdavis dot edu)) showed us an easier way to combine multiple figures into one plot using plot.new, rather than par(mfrow=...) Here’s his script: A Report Generated by knitr # plot.new() [email protected] #I discovered this plotting method when trying to add an inset figure # to a plot # plot.new is part of the traditional graphics....

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Javascript and D3 for R users, part 2: running off the R server instead of Python

October 26, 2012
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Thank you all for the positive responses to Basics of JavaScript and D3 for R Users! Quick update: last time we had to dabble in a tiny bit of Python to start a local server, in order to actually run JavaScript … Continue reading →

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Plotting correlation ellipses

October 26, 2012
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Plotting correlation ellipses

This is an oldie but a goodie. There are a lot of ways to plot multiple bivariate relationships, but this is one of my favorites, courtesy of the R Graph Gallery. https://gist.github.com/819111

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NSCB Sexy Stats Version 2

October 25, 2012
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NSCB Sexy Stats Version 2

This was a revised version of my previous post about the NSCB article. With the suggestion from Tal Galili, below were the new pie charts and the R codes to produce these plots by directly scrapping the data from the webpage using XML and RColorBrewer ...

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Using FAFSA Data to study Competitors – Part 2

October 25, 2012
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Using FAFSA Data to study Competitors – Part 2

I wanted to build upon my previous post and dive a little deeper into the sorts of questions we can answer using the FAFSA data supplied to us by applicants. As a quick overview, students completing the FAFSA for student aid can list up to ten institutions on the form. I consider this the student’s

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