Bayesian First Aid
Nice resource for NHST folks learning Bayes! http://www.sumsar.net/blog/2014/03/bayesian-first-aid-pearson-correlation-test/ (Also note *yet another* way to represent graphical models)
JAGS for MATLAB users
Kirsten found a JAGS package for MATAB!
http://psiexp.ss.uci.edu/
Also, WinBUGS (another Gibbs sampler, like JAGS) runs happily with MATLAB, in case you’re curious. https://code.google.com/p/matbugs/
Both the Lee & Wagenmakers text (http://bayesmodels.com/) and the Kruschke text (http://www.indiana.edu/~kruschke/DoingBayesianDataAnalysis/) have WinBUGS code, so that might be a good choice for those of you with data structures ready in MATLAB formats.
Excellent resources, from Jason!
Jason says:
Here is the link to all the lectures that I downloaded from that Coursera class. One of these days I’ll get around to actually watching them myself 🙂
Graphical Models
Lee and Wagenmakers: https://www.dropbox.com/s/ura5phowq8uvpb1/Lee%20and%20Wagenmakers_models.pdf
Article by Amy Perfors, including discussion of hierarchical Bayesian models: https://www.dropbox.com/s/enfglxq0pphohv6/Perfors%2C%20Tenenbaum%2C%20Wonnacott_2010_Variability%2C%20negative%20evidence%2C%20and%20the%20acquisition%20of%20verb%20argument%20constructions.pdf
Python package for generating graphical models: http://daft-pgm.org/
Another Python package, for generating network graphs (possibly of use for stealing bits of code, to modify Daft): http://networkx.github.io/
Final Meeting of the Term
It’s strange to think, but the next meeting of Bayes Club will be our last for the term. That’s right: the end of the term is approaching, and our next meeting will be during 10th week.
For our final meeting of the term, we’d like to do two things:
- Consolidate what we’ve learned by reading through some real journal articles or chapters, working together to capture some Bayesian analyses in the wild.
- Focus on any questions that you have — things that we’ve discussed that still don’t seem to make sense on even a conceptual level.
To those ends, Rose and I would like submissions for papers and/or topics and questions of discussion. If you have a Bayesian paper that you’ve been trying to figure out all term, send it in! And if any questions are burning in your mind just as much as an MCMC sampler*, send those in, as well!
If you have something in mind, please send it to Rose (rosem@uoregon.edu) and me (jleverni@uoregon.edu) by the end of this Tuesday, 2014-03-04. If you submit an idea, the three of us can meet sometime next week to try to figure it out a bit together in advance of the bigger meeting, and then you can talk in the bigger meeting for a few minutes about what headway you have made, and about what questions remain.
* (Get it? Like, an MCMC sampler “burns in”? lol.)
End of Term Reminder
Just a friendly reminder, since we’re approaching the end of winter term. If you’re taking Bayes Club for credit, you need to:
1) attend Bayes Club
2) send a one-page-ish write-up to Sanjay (sanjay@uoregon.edu) by the end of the term, describing what you’ve done and/or what you’ve learned in Bayes Club this term.
If you are signed up for credit and you think you’ll have trouble meeting one or both of these requirements, email Sanjay.
Next BayesClub: Model Comparison!
We’ll be looking at methods for comparing models using Bayesian statistics. Pretty nifty!
To get the code for an example we’ll go through, download Kruschke’s code here, and then open the file called “BernBetaModelCompJags.R”.
And check out this book chapter by Lee & Wagenmakers for more ideas.
(Here’s the site for their book by the way: http://bayesmodels.com/ Tons of good stuff.)
Bieberian inference
If you’ve thought about it, it’s on the internet. For example, a Bayesian remix of As Long As You Love Me by Justin Bieber: http://www.youtube.com/watch?v=JmSKam4BCvU
(Be sure to scroll down so you can see the lyrics.)
Bayes lecture in PSY612
Posted on behalf of Rose:
Robert is out of town this week, so Jacob and I are doing a guest lecture on Bayesian inference in PSY612: Data Analysis II. It will have a conceptual focus (vs. the more practical nuts-and-bolts focus of BayesClub), including a fair amount of discussion about the differences and similarities between Bayes and NHST. We’re building the slides in a web-ready format rather than powerpoint, so we’ll post everything publicly and you’ll be able to access the materials quite easily if you’re curious.
You’re also welcome to come sit in on the lecture, if you like! It’s Thursday 10:00am-11:20am in PLC 189. Please keep in mind that the room is not super big, and students who are registered for PSY612 need to get first priority for seats. We’re asking the 612 students to read this article before class: http://www.nature.com/news/scientific-method-statistical-errors-1.14700
Plotting
Jason asked whether R can produce 3D plots, like the posterior distribution plots Kruschke uses in his book. The answer is ohmygod yes: http://alstatr.blogspot.com/2014/02/r-animating-2d-and-3d-plots.html