Thanks. I know about Anglican, but it is not even in the same category, 
other than being Bayesian. Anglican also has MCMC, but, looking at the 
implementation, it seems it is useful only on smaller problems with 
straightforward and low-dimensional basic distributions, or discrete 
problems/distributions. I do not see how it can be used to solve even 
standard textbook examples in "real" bayesian data analysis. Otherwise, I'd 
use/improve Anglican, although its GPL license is a bit of a showstopper.

I would loved to have been able to see how far Anglican can go 
performance-wise, and stretch it to its limits, though. However, it wasn't 
obvious how to construct any of more serious data analysis problems. Having 
seen its implementation, I expect the performance comparison would make 
Bayadera shine, so I hope I'll be able to construct some examples that can 
be implemented in both environments :)

On Sunday, October 23, 2016 at 3:47:50 PM UTC+2, Boris V. Schmid wrote:
>
> Thanks Dragan.
>
> Interesting slides, and interesting section on Bayadera.  Incanter, as far 
> as I know indeed doesn't support MCMC, but there is a fairly large project 
> based on clojure that does a lot of bayesian inference.
>
> Just in case you haven't run into it:
> http://www.robots.ox.ac.uk/~fwood/anglican/examples/index.html
>
> (for the far future, there are some interesting developments happening 
> with approximate bayesian inference using neural network classification to 
> speed things up. Fun stuff.)
>
> On Thursday, October 20, 2016 at 11:38:25 PM UTC+2, Dragan Djuric wrote:
>>
>> Hi all, I posted slides for my upcoming EuroClojure talk, so you can 
>> enjoy the talk without having to take notes: 
>> http://dragan.rocks/articles/16/Clojure-is-not-afraid-of-the-GPU-slides-EuroClojure
>>
>

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