I am working on a project that requires the generation of Bernoulli outcomes. Typically, I would go about this using the built in sample() function like so: This works great and is fast, even for large n. Problem is, I want to generate each sample with its own unique probability. Seems straight forward enough, I 
I recently posted the slides from a guest lecture that I gave on Bayesian methods for biologists/ecologist. In an effort to promote active learning, the class was not a straight forward lecture, but rather a combination of informational input from me and opportunities for students to engage with the concepts via activities and discussion of 
This is a talk I gave this week in Advanced Biostatistics at McGill. The goal was to provide an gentle introduction to Bayesian methodology and to demonstrate how it is used for inference and prediction. There is a link to an accompanying R script in the slides
Some people like to do crossword puzzles. I like to do machine learning puzzles. Lucky for me, a new contest was just posted yesterday on Kaggle. So naturally, my lazy Saturday was spent getting elbow deep into the data. The training set consists of a series of ‘skies’, each containing a bunch of galaxies. Normally, 
Dispersal is a key process in many domains, and particularly in ecology. Individuals move in space, and this movement can be modelled as a random process following some kernel. The dispersal kernel is simply a probability distribution describing the distance travelled in a given time frame. Since space is continuous, it is natural to use 
This image comes from the cover of Preliminary Papers of the Second International Workshop on Artificial Intelligence and Statistics (1989). Someone abandoned it in the lobby of my building at school. Whatever for, I’ll never know. I just love the idea of machine learning/AI/Statistics evoking a robot hand drawing a best fit line through some 
A while ago I wrote this post with some R code to visualize the updating of a beta distribution as the outcome of Bernoulli trials are observed. The code provided a single plot of this process, with all the curves overlayed on top of one another. Then John Myles White (co-author of Machine Learning for 
In his 2004 paper in Trends in Ecology and Evolution, Steven Peck argues: Simulation models can be used to mimic complex systems, but unlike nature, can be manipulated in ways that would be impossible, too costly or unethical to do in natural systems. Simulation can add to theory development and testing, can offer hypotheses about the 
Why settle for just one realisation of this year’s UEFA Euro when you can let the tournament play out 10,000 times in silico? Since I already had some code lying around from my submission to the Kaggle hosted 2010 Take on the Quants challenge, I figured I’d recycle it for the Euro this year. The 
Monday, April 30, 2012 14h-16h. Stewart Biology Rm w6/12 (Montreal) guRu: Denis Haine (Université de Montréal) Topics Reproducible research was first coined by Pr. Jon Claerbout, professor of geophysics at Stanford University, to describe that the results from researches can be replicated by other scientists by making available data, procedures, materials and the computational environment 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
