Evolving notes, images and sounds by Luis Apiolaza

Category: bayesian (Page 2 of 3)

Mid-January flotsam: teaching edition

I was thinking about new material that I will use for teaching this coming semester (starting the third week of February) and suddenly compiled the following list of links:

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Doing Bayesian Data Analysis now in JAGS

Around Christmas time I presented my first impressions of Kruschke’s Doing Bayesian Data Analysis. This is a very nice book but one of its drawbacks was that part of the code used BUGS, which left mac users like me stuck.

Kruschke has now made JAGS code available so I am happy clappy and looking forward to test this New Year present. In addition, there are other updates available for the programs included in the book.

First impressions of Doing Bayesian Data Analysis

About a month ago I was discussing the approach that I would like to see in introductory Bayesian statistics books. In that post I mentioned a PDF copy of Doing Bayesian Data Analysis by John K. Kruschke and that I have ordered the book. Well, recently a parcel was waiting in my office with a spanking new, real paper copy of the book. A few days are not enough to provide a ‘proper’ review of the book but I would like to discuss my first impressions about the book, as they could be helpful for someone out there.

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Tall big data, wide big data

After attending two one-day workshops last week I spent most days paying attention to (well, at least listening to) presentations in this biostatistics conference. Most presenters were R users—although Genstat, Matlab and SAS fans were also present and not once I heard “I can’t deal with the current size of my data sets”. However, there were some complaints about the speed of R, particularly when dealing with simulations or some genomic analyses.

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If you are writing a book on Bayesian statistics

This post is somewhat marginal to R in that there are several statistical systems that could be used to tackle the problem. Bayesian statistics is one of those topics that I would like to understand better, much better, in fact. Unfortunately, I struggle to get the time to attend courses on the topic between running my own lectures, research and travel; there are always books, of course.

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