In the run-up to the French presidential election in mid-2017, G. Elliott Morris at The Crosstab published some interesting forecasts using simulated Dirichlet draws. The post in question is no longer online. It was previously available on http://www.thecrosstab.com/2017/02/14/france-2017-methodology .

The method itself is fairly well-known (see e.g. Rigdon et al. 2009, A Bayesian Prediction Model for the U.S. Presidential Election ).

I thought it would be interesting to apply the technique when the poll samples and voter base are both tiny. So I did it for Malta, which held a snap election in June 2017. The main problem here is the inconsistency of the polls. For the last few data points, I used a series of voluntary online surveys carried out by a Facebook group calling themselves MaltaSurvey. In hindsight, the survey results appear to have been biased, but at the time there was no way of knowing how to model this bias.

So, without further ado, here is the link to the code on Github.