# Monthly Archives: July 2013

## Scaling the R ecosystem: Possible Directions for Improving Dependency Versioning

July 2, 2013
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A paper published today in The R Journal discusses a fundamental limitation affecting reliability and reproducibility of R code. It explains how lack of dependency versioning causes R based applications break down, Sweave documents to stop working and CRAN to hit scaling problems. The paper suggests several solutions inspired by other open-source communities that could ...

## A Brief Look at Mixture Discriminant Analysis

July 2, 2013
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Lately, I have been working with finite mixture models for my postdoctoral work on data-driven automated gating. Given that I had barely scratched the surface with mixture models in the classroom, I am becoming increasingly comfortable with them. With this in mind, I wanted to explore their application to classification because there are times when a single class is clearly made up of...

## Parse arguments of an R script

July 2, 2013
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R can be used also as a scripting tool. We just need to add shebang in the first line of a file (script):#!/usr/bin/Rscriptand then the R code should follow.Often we want to pass arguments to such a script, which can be collected in the script by the c...

## Access individual elements of a row while using the apply function on your dataframe (or “applying down while thinking across”)

July 2, 2013
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The apply function in R is a huge work-horse for me across many projects.  My usage of it is pretty stereotypical.  Usually, I use it to make aggregations of a targeted group of columns for every row in a dataframe. … Continue reading →

July 2, 2013
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Like your .bashrc, .vimrc, or many other dotfiles you may have in your home directory, your .Rprofile is sourced every time you start an R session. On Mac and Linux, this file is usually located in ~/.Rprofile. On Windows it's buried somewhere in the R...

## There is definitely R in July

July 1, 2013
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The useR!2013 conference in Albacete, Spain, will commence next Wednesday, 10 July, and on the day before Diego and I will give a googleVis tutorial. The following Monday, 15 July, the first R in Insurance event will take place at Cass Business School ...

## Some Common Approaches for Analyzing Likert Scales and Other Categorical Data

July 1, 2013
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$Some Common Approaches for Analyzing Likert Scales and Other Categorical Data$

Analyzing Likert scale responses really comes down to what you want to accomplish (e.g. Are you trying to provide a formal report with probabilities or are you trying to simply understand the data better). Sometimes a couple of graphs are sufficient and a formalize statistical test isn’t even necessary. However, with how easy it is

## integral priors for binomial regression

July 1, 2013
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Diego Salmerón and Juan Antonio Cano from Murcia, Spain (check the movie linked to the above photograph!), kindly included me in their recent integral prior paper, even though I mainly provided (constructive) criticism. The paper has just been arXived. A few years ago (2008 to be precise), we wrote together an integral prior paper, published

## Using ESS-Remote

July 1, 2013
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If you use R and ssh into other machines a lot, e.g. for doing some big data stuff on ec2, ess-remote is a great tool. Just use M-x ssh to ssh into the remote machine, then launch R. Now just M-x ess-remote and you can use the R process just like a local process! Productivity win. Also see

## Maximum Entropy Bootstrap Rescale and Symmetrize

July 1, 2013
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R code for changing scale without changing mean or to make a probability distribution symmetric. These are commonly encountered problems by R programmers. We provide code for both of these tasks in the context of maximum entropy bootstrap (meboot) package in R.