Lately I had to write a seminar paper for a class and I decided to overdo it.But let's start at the very beginning. Here is my evolution of how I used to write stuff and how I got from this:to that:School: OpenOffice - I guess everyone has some&nb...
We continue on the linear regression chapter the book Veterinary Epidemiologic Research. Using same data as last post and running example 14.12: Now we can create some plots to assess the major assumptions of linear regression. First, let’s have a look at homoscedasticity, or constant variance of residuals. You can run a statistical test, the 
Stan 1.2.0 and RStan 1.2.0 are now available for download. See: http://mc-stan.org/ Here are the highlights. Full Mass Matrix Estimation during Warmup Yuanjun Gao, a first-year grad student here at Columbia (!), built a regularized mass-matrix estimator. This helps for posteriors with high correlation among parameters and varying scales. We’re still testing this ourselves, so
Barycentric interpolation generalises linear interpolation to arbitrary dimensions. It is very fast although suboptimal if the function is smooth. You might now it as algorithm 21.7.1 in Numerical Recipes (Two-dimensional Interpolation on an Irregular Grid). Using package geometry it can be implemented in a few lines of code in R. Here’s a quick explanation of what 
Since it seems to be the fashion, here’s a post about how I make my academic papers. Actually, who am I trying to kid? This is also about how I make slides, letters, memos and “Back in 10 minutes” signs to pin on the door. Nevertheless it’s for making academic papers that I’m going to
Hi, I presented today at INSEE R user group (FLR) how to use knitr (Sweave evolution) for writing documents which are self contained with respect to the source code: your data changed? No big deal, just compile your .Rnw file again and you are done with an updated version of your paper! is easy. Some 
Nathan Danneman (a co-author and one of my graduate students from Emory) recently sent me a New Yorker article from 2010 about the “decline effect,” the tendency for initially promising scientific results to get smaller upon replication. Wikipedia can summarize the phenomenon as well as I can: In his article, Lehrer gives several examples where 
NOTE: THIS IS NOW A PACKAGE SEE THIS LINK FOR DETAILS Let me start with a video for people who just want to see what I’m demo-ing first: I’ve been interested in speeding up workflow lately and spending a lot … Continue reading →
As I am working with large gene expression matrices (microarray data) in my job, it is sometimes important to look at the correlation in gene expression of different genes. It has been shown that by calculating the Pearson correlation between genes, one can identify (by high values, i.e. > 0.9) genes that share a common 
I cringe when I see research proposals that describe a sophisticated statistical approach, yet do not evaluate this approach in their power/precision/sample size planning. It's often the case that a simplified version of the proposed statistical approach is used instead. Presumably, this is due to the limited availability of power/precision/sample size planning software for sophisticated
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
