# Monthly Archives: March 2013

## Generating a multivariate gaussian distribution using RcppArmadillo

March 12, 2013
By

There are many ways to simulate a multivariate gaussian distribution assuming that you can simulate from independent univariate normal distributions. One of the most popular method is based on the Cholesky decomposition. Let’s see how Rcpp and Armadillo perform on this task. #include <RcppArmadillo.h> // ]using namespace Rcpp;// ] arma::mat mvrnormArma(int n, arma::vec mu, arma::mat sigma) { int ncols...

## High Resolution Figures in R

March 12, 2013
By

As I was recently preparing a manuscript for PLOS ONE, I realized the default resolution of R and RStudio images are insufficient for publication. PLOS ONE requires 300 ppi images in TIFF or EPS (encapsulated postscript) format. In R plots … Continue reading →

## R 101

March 11, 2013
By

as.character() is your friendas.character() is your friend Sometimes when you open a data file (lets say a .csv), variables will be recognized as factor whereas it should be numeric. It is therefore tempting to simply convert the variable to numeric using as.numeric(). Big mistake! If...

## Simulating Random Multivariate Correlated Data (Categorical Variables)

March 11, 2013
By

This is a repost of the second part of an example that I posted last year but at the time I only had the PDF document (written in ). This is the second example to generate multivariate random associated data. This example shows how to generate ordinal, categorical, data. It is a little more complex than generating continuous

## Interview with Boulder BI Brain Trust

March 11, 2013
By

On Friday I traveled to Boulder, CO to update the Boulder BI Brain Trust on the latest news and updates from Revolution R Enterprise. While I was there, I was interviewed by BBBT president Claudia Imhoff. In a wide-ranging chat, we discussed: What's behind the Revolution Analytics momentum over the past year? How Business Intelligence relates to Data Science...

## Simulating Allele Counts in a population using R

March 11, 2013
By

This post is inspired by the Week 7 lectures of the Coursera course "Introduction to Genetics and Evolution" (I highly recommend this course for anyone interested in genetics, BTW.) Professor Noor uses a Univ Washington software called AlleleA1 for try...

## Reproducible Research at ENAR

March 11, 2013
By

I gave a talk at the Spring ENAR meetings this morning on some of the technical aspects of creating the book. The session was on reproducible research and the slides are here. I was dinged for not using git for version control (we used dropbox for simp...

## Lipsyncing for your life: a survival analysis of RuPaul’s Drag Race

March 11, 2013
By

If you follow me on Twitter, you know that I’m a big fan of RuPaul’s Drag Race. The transformation, the glamour, the sheer eleganza extravanga is something my life needs to interrupt the monotony of grad school. I was able to catch up on nearly four seasons in a little less than a month, and I’ve been watching the… Continue reading →

## Veterinary Epidemiologic Research: Linear Regression Part 3 – Box-Cox and Matrix Representation

March 11, 2013
By
$Veterinary Epidemiologic Research: Linear Regression Part 3 – Box-Cox and Matrix Representation$

In the previous post, I forgot to show an example of Box-Cox transformation when there’s a lack of normality. The Box-Cox procedure computes values of which best “normalises” the errors. value Transformed value of Y 2 1 0.5 0 -0.5 -1 -2 For example: The plot indicates a log transformation. Matrix Representation We can use