Blog Archives

Simulating weak gravitational lensing

November 24, 2012
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Simulating weak gravitational lensing

In the search for dark matter, I have been having mixed success. It seems that locating DM in single halo skies is a fairly straightforward problem. However, when there are more than one halo, things get quite a bit trickier. As I have advocated many times before, including here and here, simulation can provide deep

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IPython vs RStudio+knitr

November 21, 2012
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IPython vs RStudio+knitr

At a meeting last night with some collaborators at the Vélobstacles project, I was excitedly told about the magic of IPython and it’s notebook functionality for reproducible research. This sounds familiar, I thought to myself. Using a literate programming approach to integrate computation with the communication of methodology and results has been at the core

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What does R do? Bring people together, of course!

November 15, 2012
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What does R do? Bring people together, of course!

Last night we had a great meet up of the Montreal R User Group. I got things started with a little presentation asking the question “What does R do?” (slides). I made the presentation using Montreal R User Group member Ramnath Vaidyanathan‘s Slidify package. Slidify allows you to generate rather handsome HTML5 slides directly using

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Did the sun just explode? The last Dutch Book you’ll ever make

November 9, 2012
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Did the sun just explode? The last Dutch Book you’ll ever make

In today’s XKCD, a pair of (presumably) physicists are told by their neutrino detector that the sun has gone nova. Problem is, the machine rolls two dice and if they both come up six it lies, otherwise it tells the truth. The Frequentist reasons that the probability of obtaining this result if the sun had

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Variable probability Bernoulli outcomes – Fast and Slow

November 1, 2012
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Variable probability Bernoulli outcomes – Fast and Slow

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

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Montreal R User Group meetup Nov. 14th

October 29, 2012
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Montreal R User Group meetup Nov. 14th

After a bit of a summer lull, the Montreal R User Group is meeting up again! We’re trying out a new venue this time. Notman House is the home of the web in Montreal. They hold hackathons and other tech user group meetups, and they are all around great people in an all around great

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Introduction to Bayesian lecture: Accompanying handouts and demos

October 19, 2012
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Introduction to Bayesian lecture: Accompanying handouts and demos

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

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Introduction to Bayesian Methods guest lecture

October 18, 2012
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Introduction to Bayesian Methods guest lecture

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

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Dark matter benchmarks: All over the map

October 14, 2012
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Dark matter benchmarks: All over the map

The three benchmark algorithms for predicting the location of dark matter halos are, for the most part, all over the map. Most of the test skies look something like this: There are, however, some skies with rather strong halo signals that get a decent amount of agreement: The Lenstool MLE algorithm is the current state

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Observing Dark Worlds – Visualizing dark matter’s distorting effect on galaxies

October 13, 2012
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Observing Dark Worlds – Visualizing dark matter’s distorting effect on galaxies

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,

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