I have made a pre-processing change to the Bayesian model. Before I explain that change, let me provide some context. Rather than resurrect my code base from the 2013 Election (I have about 40 or 50 model and processing files in that directory), I decided to code for the 2016 Election from scratch. Which is what I have done.
I had been thinking about the model output, and in particular how choppy that output appeared. To address the choppiness, I added a Henderson moving average. It worked. But it was not the most comfortable solution.
Last night, I noticed that in the lead-up to the 2013 Election, I reduced the sample size for the Morgan polls down to 1000 as an adjustment for the observed over dispersion given the sample size of the Morgan multi-mode polls. I have made this same adjustment for the 2016 models. It has had the effect of reducing the choppiness in the model. But it also means the outlier poll from the middle of 2014 no longer has such influence on the model. Consequently, the middle of 2014 is no longer the Bayesian nadir for the Coalition.
With today's Galaxy poll factored into the mix, the Bayesian model is now reporting the national voting intention at 44.6 to the Coalition, and 55.4 to Labor. This is pretty much the same result as Kevin Bonham, who puts it at 44.4 to 55.6.
Because I have made a change to the model, I will provide a fairly comprehensive set of charts.
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