Easter Trailer: Stan is coming
No Stata code this week because of the Easter break, so I thought that I would take the opportunity to trail a couple of the topics that I will be covering over the coming months. It is unusal for me to plan ahead in this way but I have been investigating a Bayesian analysis program […]
Poisson regression with two random effects: Better Mata code
Last time I presented a basic Mata program for fitting a Poisson model with two random effects to some epilepsy data. The program was faster that its Stata equivalent but slower than WinBUGS and the mixing was quite poor. This week I will try to improve the performance of the Mata program. It would make sense […]
Poisson regression with two random effects: WinBUGS, OpenBUGS and JAGS Options
In my last posting (available here) I described Stata programs that call WinBUGS, OpenBUGS or JAGS to fit a Poisson regression model with two random effects. WinBUGS, OpenBUGS and JAGS make automatic choices about the samplers that they use and in my previous comparison I accepted the defaults offered by those programs. This week I want to look […]
Poisson regression with two random effects
Here we go again There has been quite a long gap since my last post because over the New Year and for a large part of January I was visiting my daughter who is working in Colombia. It was my first time in South America and I was immediately struck by the beauty and the vitality […]
JAGS with Stata III
Merry Christmas This will be my last posting before Christmas and in January I will be abroad for a few weeks so I will not be posting again until February. I have several topics in mind for the new year, including more on JAGS, a discussion of the use of Stan and more on using […]
JAGS with Stata II
This week I want to take a more detailed look at the use of JAGS with Stata and in particular I want to contrast JAGS with WinBUGS by analysing the biopsy data that I described last time. This posting really needs to be read in sequence with the previous two. Before I start on the comparison, let […]
Modelling heart biopsies
Last week I introduced the JAGS program as an alternative to WinBUGS and this week I started with the intention of comparing JAGS and WinBUGS using a sample dataset. I decided to base the comparison on the biopsy example taken from the WinBUGS help files. Predictably, by the time that I had explained the model and fitted it […]
JAGS with Stata
WinBUGS and OpenBUGS are just two of a growing number of blackbox programs for performing Bayesian analysis. Others include, JAGS (http://mcmc-jags.sourceforge.net/), Stan (http://mc-stan.org/) and BiiPS(https://alea.bordeaux.inria.fr/biips/doku.php). Of these, the program that is closest in style to WinBUGS and OpenBUGS is JAGS; it has a similar structure and it uses very similar samplers. So it should be easy to modify the […]
Stata vs R
No Bayesian analysis this week, instead I want to talk more generally about statistical computing. I think that this discussion follows on naturally from my recent postings about linking Stata and R. As you might imagine I am quite a fan of Stata, but not one who is blinded to its limitations and for a […]
Adaptive MCMC
The Stata Journal has not published very much on Bayesian statistics, so I was delighted to see the article by Matthew Baker in the latest issue (Stata Journal 2014;14(3):623-661). Matthew describes a Mata program for adaptive MCMC and his paper has encouraged me to discuss this topic. You should certainly read that article alongside this blog. I […]
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