Modelling the Modeller

Something I’ve struggled with on and off over the 20 years that I have been making mathematical models is explaining those models to others. I have tried to bring people along and develop their understanding. But mainly what I observed was that, some people just got it and others did not.

I have certainly improved my own skill at explaining. This comes down to having streamlined stories and simpler take-home messages. Telling a clearer story certainly improves my audiences’ self-satisfaction, but ultimately some of them get the whole message and others do not.

Continue reading “Modelling the Modeller”

Predictive Models

I have mentioned, in the past, that I am a huge fan of Nate Silver. Something which he used to repeat quite frequently, on their podcast, is a sort of predictive modelling tautology:

The best prediction of the future is no change.

Nate Silver [Paraphrasing]

This concept has even got a probabilistic and philosophical theory behind it. All other things being equal, over the long history of time, the next moment from now is not likely to be any different from right now. If we repeat this process often enough then we will be right more often than we are wrong. In essence, we are accepting that there is continuity (and perhaps causality) in our experience of the natural world. Political scientist David Runciman even explored the concept in his recent work of political theory.

I originally took this statement in the manner in which, I hope, it was intended. But behind every great phrase there is often an enticing problem. Thinking over this phrase has led me to realise that there are three basic types of predictive models and each one of them has a fundamentally different purpose and indeed parameterisation.

Continue reading “Predictive Models”